Good Discriminative Capacity Research Articles

Development of a Genomic Metric That Can Be Rapidly Used to Predict Clinical Outcome in Severely Injured Trauma Patients*

Many patients have complicated recoveries following severe trauma due to the development of organ injury. Physiological and anatomical prognosticators have had limited success in predicting clinical trajectories. We report on the development and retrospective validation of a simple genomic composite score that can be rapidly used to predict clinical outcomes. Retrospective cohort study. Multi-institutional level 1 trauma centers. Data were collected from 167 severely traumatized (injury severity score >15) adult (18-55 yr) patients. Microarray-derived genomic data obtained from 167 severely traumatized patients over 28 days were assessed for differences in messenger RNA abundance among individuals with different clinical trajectories. Once a set of genes was identified based on differences in expression over the entire study period, messenger RNA abundance from these subjects obtained in the first 24 hours was analyzed in a blinded fashion using a rapid multiplex platform, and genomic data reduced to a single metric. From the existing genomic dataset, we identified 63 genes whose leukocyte expression differed between an uncomplicated and complicated clinical outcome over 28 days. Using a multiplex approach that can quantitate messenger RNA abundance in less than 12 hours, we reassessed total messenger RNA abundance from the first 24 hours after trauma and reduced the genomic data to a single composite score using the difference from reference. This composite score showed good discriminatory capacity to distinguish patients with a complicated outcome (area under a receiver-operator curve, 0.811; p <0.001). This was significantly better than the predictive power of either Acute Physiology and Chronic Health Evaluation II or new injury severity score scoring systems. A rapid genomic composite score obtained in the first 24 hours after trauma can retrospectively identify trauma patients who are likely to develop complicated clinical trajectories. A novel platform is described in which this genomic score can be obtained within 12 hours of blood collection, making it available for clinical decision making.

Fiabilidad y validez del Copenhagen Burnout Inventory para su uso en España

The Copenhagen Burnout Inventory (CBI) is a public domain questionnaire measuring the degree of psychological fatigue experienced in three subdimensions of Burnout: personal (PB), work-related (WB), and client-related Burnout (CB). The study aimed to examine the acceptability, reliability and construct validity of the Spanish version of CBI. The study population consisted of 479 workers of educational centers, social work centres, healthcare centres and workers within the industry sector. Data was collected in 2009 through a self-administered questionnaire including the three CBI scales, sixteen scales of psychosocial work environment (COPSOQ ISTAS21) and perceived general and mental health and vitality (SF-36). Response rate was 78.7%. The three scales have an inter-item correlation average between 0.42 and 0.60 and a corrected item-total correlation between 0,49 and 0,83. The internal consistency of the three scales had Cronbach's α values of 0.90 for PB, 0.83 for WB and 0.82 for CB. Burnout was related to both psychosocial work environment and wellbeing measures in the expected direction and intensity. The items of the three scales show good discrimination capacity, good consistency and homogeneity. The three CBI scales have an acceptable internal consistency reliability index, slightly higher in PB. The discrimination capacity of the scales is verified through the discrimination index and the different levels between occupations and activities. These results demonstrate that the Spanish version of the CBI is a reliable and valid instrument for measuring Burnout.

Relating health-related Quality of Life to disability progression in multiple sclerosis, using the 5-level EQ-5D

Background: Increasing use of the Quality-Adjusted Life-Year to inform resource allocation decision-making has highlighted the importance of relating clinical and health-related quality of life (HRQoL) outcomes in multiple sclerosis (MS) patients. Objective and Methods: To investigate the relationship between the Expanded Disability Status Scale (EDSS) and HRQoL utility, using the 5-level EQ-5D (EQ-5D-5L). The discriminatory power of the EQ-5D-5L was assessed using Shannon’s indices. Results: A linear decline in utility was observed with changes in EDSS score from 0 to 6, after which point the relationship exhibited greater variability. Mean utility values ranged from −0.22 at EDSS 9 to 0.88 at EDSS 0. We found that the discriminative capacity of the EQ-5D-5L was considerably lower for the domains self-care and anxiety/depression, compared with other health-related domains. Conclusion: In its first reported use in an MS population, the EQ-5D-5L displayed good discriminatory capacity, although performance differed between the various domains of health, with evidence of a ceiling effect present in the domains of self-care and anxiety/depression. The EQ-5D-5L demonstrated a high correlation with EDSS in our MS cohort up to EDSS 6, after which point the utility valuation of severe health states exhibited much greater variability. Utility estimates from this study may be used in economic evaluations of disease-modifying therapies in MS, to inform resource-allocation decisions.

Inertial sensor motion analysis of gait, sit–stand transfers and step-up transfers: differentiating knee patients from healthy controls

Patients undergoing total knee replacement for end stage knee osteoarthritis (OA) become increasingly younger and more demanding. Consequently, outcome assessment tools need to evolve toward objective performance-based measures. We applied a novel approach toward ambulatory biomechanical assessment of physical function using a single inertial sensor located at the pelvis to derive various motion parameters during activities of daily living. We investigated the potential of a clinically feasible battery of tests to define relevant parameters of physical function. We compared preoperative measures of end stage knee OA patients to healthy subjects. Our results show that measures of time yield the highest discriminative capacity to differentiate between groups. Additionally we found disease-dependent and task-specific alterations of movement for inertial sensor-derived motion parameters with good discriminative capacity. The inertial sensor's output quantities seem to capture another clinically relevant dimension of physical function that is supplementary to time. This study demonstrates the potential of inertial sensor-based motion analysis and provides a standardized test feasible for a routine clinical application in the longitudinal follow-up.

FRAX® tool, the WHO algorithm to predict osteoporotic fractures: the first analysis of its discriminative and predictive ability in the Spanish FRIDEX cohort.

BackgroundThe WHO has recently published the FRAX® tool to determine the absolute risk of osteoporotic fracture at 10 years. This tool has not yet been validated in Spain.Methods/designA prospective observational study was undertaken in women in the FRIDEX cohort (Barcelona) not receiving bone active drugs at baseline. Baseline measurements: known risk factors including those of FRAX® and a DXA. Follow up data on self-reported incident major fractures (hip, spine, humerus and wrist) and verified against patient records. The calculation of absolute risk of major fracture and hip fracture was by FRAX® website. This work follows the guidelines of the STROBE initiative for cohort studies. The discriminative capacity of FRAX® was analyzed by the Area Under Curve (AUC), Receiver Operating Characteristics (ROC) and the Hosmer-Lemeshow goodness-of-fit test. The predictive capacity was determined using the ratio of observed fractures/expected fractures by FRAX® (ObsFx/ExpFx).ResultsThe study subjects were 770 women from 40 to 90 years of age in the FRIDEX cohort. The mean age was 56.8 ± 8 years. The fractures were determined by structured telephone questionnaire and subsequent testing in medical records at 10 years. Sixty-five (8.4%) women presented major fractures (17 hip fractures). Women with fractures were older, had more previous fractures, more cases of rheumatoid arthritis and also more osteoporosis on the baseline DXA. The AUC ROC of FRAX® for major fracture without bone mineral density (BMD) was 0.693 (CI 95%; 0.622-0.763), with T-score of femoral neck (FN) 0.716 (CI 95%; 0.646-0.786), being 0.888 (CI 95%; 0.824-0.952) and 0.849 (CI 95%; 0.737-0.962), respectively for hip fracture. In the model with BMD alone was 0.661 (CI 95%; 0.583-0.739) and 0.779 (CI 95%; 0.631-0.929). In the model with age alone was 0.668 (CI 95%; 0.603-0.733) and 0.882 (CI 95%; 0.832-0.936). In both cases there are not significant differences against FRAX® model. The overall predictive value for major fracture by ObsFx/ExpFx ratio was 2.4 and 2.8 for hip fracture without BMD. With BMD was 2.2 and 2.3 respectively. Sensitivity of the four was always less than 50%. The Hosmer-Lemeshow test showed a good correlation only after calibration with ObsFx/ExpFx ratio.ConclusionsThe current version of FRAX® for Spanish women without BMD analzsed by the AUC ROC demonstrate a poor discriminative capacity to predict major fractures but a good discriminative capacity for hip fractures. Its predictive capacity does not adjust well because leading to underdiagnosis for both predictions major and hip fractures. Simple models based only on age or BMD alone similarly predicted that more complex FRAX® models.

Comparison of Traditional Cardiovascular Risk Models and Coronary Atherosclerotic Plaque as Detected by Computed Tomography for Prediction of Acute Coronary Syndrome in Patients With Acute Chest Pain

The objective was to determine the association of four clinical risk scores and coronary plaque burden as detected by computed tomography (CT) with the outcome of acute coronary syndrome (ACS) in patients with acute chest pain. The hypothesis was that the combination of risk scores and plaque burden improved the discriminatory capacity for the diagnosis of ACS. The study was a subanalysis of the Rule Out Myocardial Infarction Using Computer-Assisted Tomography (ROMICAT) trial-a prospective observational cohort study. The authors enrolled patients presenting to the emergency department (ED) with a chief complaint of acute chest pain, inconclusive initial evaluation (negative biomarkers, nondiagnostic electrocardiogram [ECG]), and no history of coronary artery disease (CAD). Patients underwent contrast-enhanced 64-multidetector-row cardiac CT and received standard clinical care (serial ECG, cardiac biomarkers, and subsequent diagnostic testing, such as exercise treadmill testing, nuclear stress perfusion imaging, and/or invasive coronary angiography), as deemed clinically appropriate. The clinical providers were blinded to CT results. The chest pain score was calculated and the results were dichotomized to ≥10 (high-risk) and <10 (low-risk). Three risk scores were calculated, Goldman, Sanchis, and Thrombolysis in Myocardial Infarction (TIMI), and each patient was assigned to a low-, intermediate-, or high-risk category. Because of the low number of subjects in the high-risk group, the intermediate- and high-risk groups were combined into one. CT images were evaluated for the presence of plaque in 17 coronary segments. Plaque burden was stratified into none, intermediate, and high (zero, one to four, and more than four segments with plaque). An outcome panel of two physicians (blinded to CT findings) established the primary outcome of ACS (defined as either an acute myocardial infarction or unstable angina) during the index hospitalization (from the presentation to the ED to the discharge from the hospital). Logistic regression modeling was performed to examine the association of risk scores and coronary plaque burden to the outcome of ACS. Unadjusted models were individually fitted for the coronary plaque burden and for Goldman, Sanchis, TIMI, and chest pain scores. In adjusted analyses, the authors tested whether the association between risk scores and ACS persisted after controlling for the coronary plaque burden. The prognostic discriminatory capacity of the risk scores and plaque burden for ACS was assessed using c-statistics. The differences in area under the receiver-operating characteristic curve (AUC) and c-statistics were tested by performing the -2 log likelihood ratio test of nested models. A p value <0.05 was considered statistically significant. Among 368 subjects, 31 (8%) subjects were diagnosed with ACS. Goldman (AUC = 0.61), Sanchis (AUC = 0.71), and TIMI (AUC = 0.63) had modest discriminatory capacity for the diagnosis of ACS. Plaque burden was the strongest predictor of ACS (AUC = 0.86; p < 0.05 for all comparisons with individual risk scores). The combination of plaque burden and risk scores improved prediction of ACS (plaque + Goldman AUC = 0.88, plaque + Sanchis AUC = 0.90, plaque + TIMI AUC = 0.88; p < 0.01 for all comparisons with coronary plaque burden alone). Risk scores (Goldman, Sanchis, TIMI) have modest discriminatory capacity and coronary plaque burden has good discriminatory capacity for the diagnosis of ACS in patients with acute chest pain. The combined information of risk scores and plaque burden significantly improves the discriminatory capacity for the diagnosis of ACS.

Geomatics Use in the Evaluation of Surface Qualities Degradation in Saline Area (The case of the lower Cheliff plain)

The plain of the lower Cheliff is located 220km to the west of Algiers and extends over 60000ha. This plain which is only 40km far from the Mediterranean has an arid climate and has suffered from dangerous degradation problems of its physical environment. This degradation is essentially due to the soil salinization which is manifested in different ground surfaces in relation with the degradation levels. The aim of this work is to use remote-sensing to evaluate the levels of soil degradation by the identification and the mapping of the ground surface. The visual analysis of the Aster image (August 2005) allows us to extract the big agronomic landscape units. And this led us to identify four homogeneous areas representing the different ground surfaces of the plain. The two irrigated perimeters of Ouarizane and Djediouia, the non saline soils of Benziane valley, and the Gaa which contain uncultivated saline soils with halophytic vegetation. The supervised classification of the satellite image allows us to generalize this good discrimination capacity to the whole ground surface and to obtain 9 homogeneous classes corresponding to various degradation levels. Therefore it is evaluated by soil and vegetal cover indicators. The remote-sensing data with salinity measured data of the ground surface classes has been used to map the soil salinity using remote-sensing and apply a comparison with the map obtained by ordinary kriging. The two methods have shown an important extension of the salinity. However, the estimated salinity map by remote-sensing made it possible to better estimate in comparison to the one obtained by ordinary kriging, on the level of extremes values.

Pilot evaluation of the psychometric properties of a self-medication Risk Assessment Tool among elderly patients in a community setting

BackgroundAlthough community pharmacists in the United Kingdom are expected to assess elderly patients' needs for additional support in managing their medicines, there is limited data on potentially useful assessment tools. We sought to evaluate a 13-item assessment instrument among community dwelling elderly patients, 65 years and above. The instrument is composed of a cognitive risk sub-scale of 6 items and a physical risk sub-scale of 7 items.FindingsThe instrument was administered to elderly patients in a survey performed in a community to the west of Glasgow, Scotland. The survey recruited 37 participants, 31 from 4 community pharmacies and 6 patients whose medication management tasks were managed by the West Glasgow Community Health and Care Partnership (managed patients). Community pharmacists independently rated 29 of the 37 participants' comprehension of, and dexterity in handling their medicines. We assessed scale reliability, convergent validity and criterion validity. In sub-analyses, we assessed differences in scores between the managed patients and those recruited from the community pharmacies, and between multi-compartment compliance aid users and non-users. The instrument showed satisfactory internal consistency (Cronbach's alpha of 0.792 for 13-item scale). There was significant strong negative correlation between the cognitive risk sub-scores and community pharmacists' assessment of comprehension (ρ = -0.546, p = 0.0038); and physical risk sub-scores and community pharmacists' assessment of dexterity (ρ = -0.491, p = 0.0093). The Area Under the Receiver Operator Characteristic Curve (AUC ± SE; 95%CI) showed that the instrument had good discriminatory capacity (0.86 ± 0.07; 0.68, 0.96). The best cut-off (sensitivity, specificity) was ≥4 (65%, 100%). In the sub-analyses, managed patients had significantly higher cognitive risk sub-scores (6.5 versus 4.0, p = 0.0461) compared to non-managed patients. There was a significant difference in total risk score (4 versus 2, p = 0.0135) and cognitive risk sub-score (4 versus 1.5, p = 0.0029) between users and non-users of multi-compartment compliance aids.ConclusionsThis instrument shows potential for use in identifying elderly patients who may have problems managing their own medicines in the community setting. However, more robust validity and reliability assessments are needed prior to introduction of the tool into routine practice.

Hospital deaths and adverse events in Brazil

BackgroundAdverse events are considered a major international problem related to the performance of health systems. Evaluating the occurrence of adverse events involves, as any other outcome measure, determining the extent to which the observed differences can be attributed to the patient's risk factors or to variations in the treatment process, and this in turn highlights the importance of measuring differences in the severity of the cases. The current study aims to evaluate the association between deaths and adverse events, adjusted according to patient risk factors.MethodsThe study is based on a random sample of 1103 patient charts from hospitalizations in the year 2003 in 3 teaching hospitals in the state of Rio de Janeiro, Brazil. The methodology involved a retrospective review of patient charts in two stages - screening phase and evaluation phase. Logistic regression was used to evaluate the relationship between hospital deaths and adverse events.ResultsThe overall mortality rate was 8.5%, while the rate related to the occurrence of an adverse event was 2.9% (32/1103) and that related to preventable adverse events was 2.3% (25/1103). Among the 94 deaths analyzed, 34% were related to cases involving adverse events, and 26.6% of deaths occurred in cases whose adverse events were considered preventable. The models tested showed good discriminatory capacity. The unadjusted odds ratio (OR 11.43) and the odds ratio adjusted for patient risk factors (OR 8.23) between death and preventable adverse event were high.ConclusionsDespite discussions in the literature regarding the limitations of evaluating preventable adverse events based on peer review, the results presented here emphasize that adverse events are not only prevalent, but are associated with serious harm and even death. These results also highlight the importance of risk adjustment and multivariate models in the study of adverse events.

Piloting the Perinatal Obsessive-Compulsive Scale (POCS): Development and validation

Onset/worsening of obsessive-compulsive disorder (OCD) during the perinatal period are frequently seen clinically. No specific tool assessing the unique content, context, severity, and onset of perinatal OCD exists. A self-report scale of perinatal obsessions and compulsions, the Perinatal Obsessive-Compulsive Scale (POCS), was developed and validated. A total of 162 women (67 pregnant, 95 postpartum) participated in this pilot study. They completed the POCS as well as the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). The POCS has good construct validity, reflected by representative items, high internal consistency, good concurrent validity and discriminative capacity. The most common obsessions were fear of having an unhealthy baby at birth, contamination, the baby being taken away, and infant death. Behavioral compulsions such as repeating rituals, asking for reassurance, checking, and cleaning mirrored these obsessions. The POCS helps clinicians detect perinatal OCD while giving perinatal women an opportunity to openly discuss socially sensitive issues.

An Australian risk prediction model for determining early mortality following aortic valve replacement

To develop a multivariable logistic risk model for predicting early mortality following aortic valve replacement (AVR) in adults, and to compare its performance against existing AVR-dedicated models. Prospectively collected data from the Australasian Society of Cardiac and Thoracic Surgeons (ASCTS) database project were used. Thirty-five preoperative variables from AVR literature were considered for analysis by chi-square method and multiple logistic regression. Using the bootstrap re-sampling technique for variable selection, five plausible models were identified. Based on models' calibration, discrimination and predictive capacity during n-fold validation, a final model, the AVR-Score, was chosen. An additive score, derived from the final model, was also validated externally in a consecutive cohort. The performance of AVR-dedicated risk models from the North West Quality Improvement Program (NWQIP) and the Northern New England Cardiovascular Study (NNE) groups were also assessed using the receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow (H-L) chi-square test. Between July 2001 and June 2008, a total of 3544 AVR procedures were performed. Early mortality was 4.15%. The AVR-Score contained the following predictors: age, New York Heart Association class, left main disease, infective endocarditis, cerebrovascular disease, renal dysfunction, previous cardiac surgery and estimated ejection fraction. Our final model (AVR-Score) obtained an average area under ROC curve of 0.78 (95% confidence interval (CI): 0.76, 0.80) and an H-L p-value of 0.41 (p>0.05) during internal validation, indicating good discrimination and calibration capacity. External validation of the additive score on a consecutive cohort of 1268 procedures produced an ROC of 0.73 (0.62, 0.84) and an H-L p-value of 0.48 (p>0.05). The NWQIP and NNE risk models achieved acceptable discrimination of ROC of 0.77 (0.73, 0.81). However, both models obtained H-L p-values of 0.002 (p<0.05), indicating a poor fit in our cohort. Existing AVR-dedicated risk models were deemed inappropriate for risk prediction in the Australian population. A preoperative risk model was developed using prospective data from a contemporary AVR cohort.

Prognostic model for survival in patients with early stage cervical cancer

In the management of early stage cervical cancer, knowledge about the prognosis is critical. Although many factors have an impact on survival, their relative importance remains controversial. This study aims to develop a prognostic model for survival in early stage cervical cancer patients and to reconsider grounds for adjuvant treatment. A multivariate Cox regression model was used to identify the prognostic weight of clinical and histological factors for disease-specific survival (DSS) in 710 consecutive patients who had surgery for early stage cervical cancer (FIGO [International Federation of Gynecology and Obstetrics] stage IA2-IIA). Prognostic scores were derived by converting the regression coefficients for each prognostic marker and used in a score chart. The discriminative capacity was expressed as the area under the curve (AUC) of the receiver operating characteristic. The 5-year DSS was 92%. Tumor diameter, histological type, lymph node metastasis, depth of stromal invasion, lymph vascular space invasion, and parametrial extension were independently associated with DSS and were included in a Cox regression model. This prognostic model, corrected for the 9% overfit shown by internal validation, showed a fair discriminative capacity (AUC, 0.73). The derived score chart predicting 5-year DSS showed a good discriminative capacity (AUC, 0.85). In patients with early stage cervical cancer, DSS can be predicted with a statistical model. Models, such as that presented here, should be used in clinical trials on the effects of adjuvant treatments in high-risk early cervical cancer patients, both to stratify and to include patients.

T1291 A Novel Quantitative Severity Score to Stratify Hospitalizations for Crohn's Disease

Introduction: There are limited tools to stratify severity of Crohn's disease(CD) hospitalizations. Existing co-morbidity indices were developed to predict mortality, a rare outcome in this cohort. A CD-specific quantitative risk stratification tool that predicts more common and relevant outcomes such may be of greater use. Methods: We used data from the Nationwide Inpatient Sample (NIS) 2004, a national hospital discharge database, to identify CD-related hospitalizations using diagnosis codes. “Severe hospitalizations” were defined as those resulting in non-elective bowel surgery or hospitalization for longer than 7 days. Independent predictors of severity were identified through multivariate regression and assigned quantitative weights based on their regression coefficients with the sum representing the cumulative score. Results: There were 25,938 CD discharges among which 6,169(23.8%) were severe. Table 1 presents the weights of the individual components of the severity score. The cumulative severity score ranged from 0-13 points. A total of 15,330(59.1%), 9,060(34.9%) and 1,548(6.0%) discharges were classified as being low, intermediate, and high risk for severe disease respectively. The intermediate(OR 2.63, 95%CI 2.47-2.80) and high risk categories(OR 13.62, 95% CI 12.12-15.33) were associated with a significantly higher odds of severe hospitalization. The model had good discriminative capacity(AUC 0.68) for severe disease. Validation in an independent cohort of hospitalized CD patients from NIS 2007 revealed comparable performance. Existing co-morbidity indices performed poorly in predicting severe hospitalizations (AUC<0.55). Conclusion: Using administrative data, we propose a simple quantitative severity score to stratify CD hospitalizations and predict relevant CD-related outcomes. Table 1: Severity score to stratify Crohn's disease hospitalizations

T1292 A Simple Quantitative Score to Stratify Severity of Ulcerative Colitis Hospitalizations

Introduction: There are limited tools to stratify severity of Crohn's disease(CD) hospitalizations. Existing co-morbidity indices were developed to predict mortality, a rare outcome in this cohort. A CD-specific quantitative risk stratification tool that predicts more common and relevant outcomes such may be of greater use. Methods: We used data from the Nationwide Inpatient Sample (NIS) 2004, a national hospital discharge database, to identify CD-related hospitalizations using diagnosis codes. “Severe hospitalizations” were defined as those resulting in non-elective bowel surgery or hospitalization for longer than 7 days. Independent predictors of severity were identified through multivariate regression and assigned quantitative weights based on their regression coefficients with the sum representing the cumulative score. Results: There were 25,938 CD discharges among which 6,169(23.8%) were severe. Table 1 presents the weights of the individual components of the severity score. The cumulative severity score ranged from 0-13 points. A total of 15,330(59.1%), 9,060(34.9%) and 1,548(6.0%) discharges were classified as being low, intermediate, and high risk for severe disease respectively. The intermediate(OR 2.63, 95%CI 2.47-2.80) and high risk categories(OR 13.62, 95% CI 12.12-15.33) were associated with a significantly higher odds of severe hospitalization. The model had good discriminative capacity(AUC 0.68) for severe disease. Validation in an independent cohort of hospitalized CD patients from NIS 2007 revealed comparable performance. Existing co-morbidity indices performed poorly in predicting severe hospitalizations (AUC<0.55). Conclusion: Using administrative data, we propose a simple quantitative severity score to stratify CD hospitalizations and predict relevant CD-related outcomes. Table 1: Severity score to stratify Crohn's disease hospitalizations

Identification of failure type in corroded pipelines: A Bayesian probabilistic approach

Spillover of hazardous materials from transport pipelines can lead to catastrophic events with serious and dangerous environmental impact, potential fire events and human fatalities. The problem is more serious for large pipelines when the construction material is under environmental corrosion conditions, as in the petroleum and gas industries. In this way, predictive models can provide a suitable framework for risk evaluation, maintenance policies and substitution procedure design that should be oriented to reduce increased hazards. This work proposes a Bayesian probabilistic approach to identify and predict the type of failure (leakage or rupture) for steel pipelines under realistic corroding conditions. In the first step of the modeling process, the mechanical performance of the pipe is considered for establishing conditions under which either leakage or rupture failure can occur. In the second step, experimental burst tests are used to introduce a mean probabilistic boundary defining a region where the type of failure is uncertain. In the boundary vicinity, the failure discrimination is carried out with a probabilistic model where the events are considered as random variables. In turn, the model parameters are estimated with available experimental data and contrasted with a real catastrophic event, showing good discrimination capacity. The results are discussed in terms of policies oriented to inspection and maintenance of large-size pipelines in the oil and gas industry.

Use of Fourier transform infrared spectroscopy and chemometrics to discriminate clinical isolates of bacteria of the Burkholderia cepacia complex from different species and ribopatterns

A methodology for the discrimination of Burkholderia cepacia complex (Bcc) clinical isolates at the species level and at the ribopattern level using Fourier transform infrared (FTIR) spectroscopy and chemometrics analysis was assessed in this study. Different Bcc sequential isolates collected at the Santa Maria Hospital (HSM), in Portugal, from clinically infected cystic fibrosis (CF) patients were previously classified by established molecular methods at the species level and differentiated at the strain level, based on their ribopatterns. A set of 185 of these isolates, representing four different Bcc species (Burkholderia cepacia, Burkholderia cenocepacia (recA lineages III-A and III-B), Burkholderia multivorans and Burkholderia stabilis), was analyzed by FTIR and results were processed with chemometric methods. Ten reference strains of these species were used to test the FTIR method. The discrimination at the species level led to misclassification error rates of 10% and 32% for the HSM isolates and reference strains, respectively, clearly indicating that the FTIR classification method was unable to generalize results for the reference strains. Infrared spectra of HSM isolates were further analyzed in terms of the discrimination according to the ribopattern. Results showed misclassification error rates of 4%, 2%, and 8% for B. cepacia, B. cenocepacia III-A, and B. cenocepacia III-B ribopatterns, respectively. These results demonstrated good FTIR spectroscopy discrimination capacity at the ribopattern level, for the HSM isolates but showed difficulty at the species level, especially when the reference strains were included. Remarkably, this methodology was found to discriminate isolates belonging to the same species and ribopattern that were collected from the same patient during prolonged colonization, opening the door to the identification of chemical modifications resulting from adaptation strategies to the CF lung stressing environment, in particular to aggressive and prolonged antibiotic therapy.

TIPS for Budd-Chiari Syndrome: Long-Term Results and Prognostics Factors in 124 Patients

Budd-Chiari syndrome (BCS) is a rare and life-threatening disorder secondary to hepatic venous outflow obstruction. Small series of BCS patients indicate that transjugular intrahepatic portosystemic shunt (TIPS) may be useful. However, the influence of TIPS on patient survival and factors that predict the outcome of TIPS in BCS patients remain unknown. One hundred twenty-four consecutive BCS patients treated with TIPS in 6 European centers between July 1993 and March 2006 were followed until death, orthotopic liver transplantation (OLT), or last clinical evaluation. Prior to treatment with TIPS, BCS patients had a high Model of End Stage Liver Disease and high Rotterdam BCS prognostic index (98% of patients at intermediate or high risk) indicating severity of liver dysfunction. However, 1- and 5-year OLT-free survival were 88% and 78%, respectively. In the high-risk patients, 5-year OLT-free survival was much better than that estimated by the Rotterdam BCS index (71% vs 42%, respectively). In the whole population, bilirubin, age, and international normalized ratio for prothrombin time independently predicted 1-year OLT-free survival. A prognostic score with a good discriminative capacity (area under the curve, 0.86) was developed from these variables. Seven out of 8 patients with a score >7 died or underwent transplantation vs 5 out of 114 patients with a score <7. Long-term outcome for patients with severe BCS treated with TIPS is excellent even in high-risk patients, suggesting that TIPS may improve survival. Furthermore, we identified a small subgroup of BCS patients with poor prognosis despite TIPS who might benefit from early OLT.

Adaptation and validation of the Spanish version of the Mood Disorder Questionnaire for the detection of bipolar disorder

The Mood Disorder Questionnaire (MDQ) is an instrument for the detection of patients with bipolar disorder (BD). The original English version is validated in both the psychiatric and the general population, but a validated Spanish version is not yet available. Psychometric properties of the Spanish adaptation of the MDQ in psychiatry are described. The MDQ is a self-administered questionnaire comprising a list of 13 hypomanic symptoms and two questions about concurrence of symptoms and functional impairment caused by the symptoms. We selected patients from 15 psychiatric outpatient departments, diagnosed with BD type I and II (BDI and BDII) and major depression (MD) according to DSM-IV-TR criteria (concurrent validity instrument). A control group of healthy subjects (HS) was selected. The patient-selection criteria included stability of the disorder and pharmacological treatment. The MDQ was administered to 236 subjects, distributed among the four groups, on two occasions, four weeks apart. We analysed the internal consistency, test-retest reliability, and discriminative capacity of the MDQ for the detection of patients with BD. Concurrent validity based on diagnosis according to DSM-IV-TR was 0.83. The internal consistency, evaluated by Cronbach's alpha, was 0.90. The mean (SD) number of affirmative responses by group was: 9.8 (2.4) for BDI, 8.5 (2.8) for BDII, 2.7 (2.2) for MD, and 1.02 (1.9) for HS. Statistically significant differences between all the groups were found (Kruskal-Wallis test, p < 0.001). Concurrent validity using the diagnostic variable was 0.83. Test-retest reliability was 0.92. We analysed the scale's discriminative capacity, revealing a sensitivity value of 0.60 [95% confidence interval (CI) = 0.51-0.69] and a specificity value of 0.98 (95% CI = 0.94-0.99) in the detection of BD. The positive and negative probability ratios were 35.5 and 2.4, respectively. If we consider only seven positive responses as the discriminative criterion, sensitivity increases to 0.81 (95% CI = 0.73-0.88), the specificity value is 0.95 (95% CI = 0.89-0.98) and the positive and negative probability quotients are 16 and 5.3. The psychometric characteristics of the Spanish version are similar to those of the original version. In the Spanish adaptation of the MDQ, seven positive responses to hypomanic symptoms show a good discriminative capacity for BD in patients attending psychiatric outpatient facilities; therefore, this cut-off score is proposed for the detection of BD in psychiatric outpatients.

New Accelerometric Method to Discriminate Between Asymptomatic Subjects and Patients With Medial Knee Osteoarthritis During 3-D Gait

This study presents a new method to estimate 3-D linear accelerations at tibial and femoral functional coordinate systems. The method combines the use of 3-D accelerometers, 3-D gyroscopes and reflective markers rigidly fixed on an exoskeleton and, a functional postural calibration method. Marker positions were tracked by a six-camera optoelectronic system (VICON 460, Oxford Metrics). The purpose of this study was to determine if this method could discriminate between medial osteoarthritic and asymptomatic knees during gait. Nine patients with osteoarthritic knees and nine asymptomatic control subjects were included in this study. Eighteen parameters representing maximal, minimal, and range of acceleration values were extracted during the loading and preswing to mid-swing phase periods, and were compared in both groups. Results show good discriminative capacity of the new method. Eight parameters were significantly different between both groups. The proposed method has the potential to be used in comprehending and monitoring gait strategy in patients with osteoarthritic knee.

Psychometric properties of the SESM, Italian version of the “Consumer constructed Scale to measure empowerment among users of mental health services” (Rogers et al., 1997)

To present the psychometric properties of the "Consumer-constructed Scale to measure empowerment" (Rogers et al., 1997) Italian version. After briefly recollecting "history", contents and psychometric features of the original scale, proceeding from Straticò & Degli Esposti's translation (2002), in this paper, the psychometric properties of the Italian version are described. The text of the instrument has been brought for discussion in a users' focus group and subsequently tested for reliability study; a second focus group followed to reach the definitive Italian version. The Italian version of the Scale, consists of 28 items, showed an adequate internal consistency and reliability both for the whole scale and for most of the items, which have shown to have also good discriminative capacity. SESM can be an useful instrument to give empiric evidence supporting empowerment concept. Considering the results, it can be a qualifying and irreplaceable instrument for "empowered condition" evaluation.