The role of psychological stress in inflammatory bowel disease: quality assessment of methods of 18 prospective studies and suggestions for future research

BACKGROUND: Enquiries among patients on the one hand and experimental and observational studies on the other suggest an influence of stress on inflammatory bowel diseases (IBD). However, since this influence remains hypothetical, further research is essential. We aimed to devise recommendations for future investigations in IBD by means of scrutinizing previously applied methodology. METHODS: We critically reviewed prospective clinical studies on the effect of psychological stress on IBD. Eligible studies were searched by means of the PubMed electronic library and through checking the bibliographies of located sources. RESULTS: We identified 20 publications resulting from 18 different studies. Sample sizes ranged between 10 and 155 participants. Study designs in terms of patient assessment, control variables, and applied psychometric instruments varied substantially across studies. Methodological strengths and weaknesses were irregularly dispersed. Thirteen studies reported significant relationships between stress and adverse outcomes. CONCLUSIONS: Study designs, including accuracy of outcome assessment and repeated sampling of outcomes (i.e. symptoms, clinical, and endoscopic), depended upon conditions like sample size, participants' compliance, and available resources. Meeting additional criteria of sound methodology, like taking into account covariates of the disease and its course, is strongly recommended to possibly improve study designs in future IBD research.

Accuracy and reproducibility of aortic annulus sizing using a dedicated three-dimensional computed tomography reconstruction tool in patients evaluated for transcatheter aortic valve replacement

Aims: To evaluate the accuracy and reproducibility of aortic annulus sizing using a multislice computed tomography (MSCT) based aortic root reconstruction tool compared with conventional imaging among patients evaluated for transcatheter aortic valve replacement (TAVR). Methods and results: Patients referred for TAVR underwent standard preprocedural assessment of aortic annulus parameters using MSCT, angiography and transoesophageal echocardiography (TEE). Three-dimensional (3-D) reconstruction of MSCT images of the aortic root was performed using 3mensio (3mensio Medical Imaging BV, Bilthoven, The Netherlands), allowing for semi-automated delineation of the annular plane and assessment of annulus perimeter, area, maximum, minimum and virtual diameters derived from area and perimeter (aVD and pVD). A total of 177 patients were enrolled. We observed a good inter-observer variability of 3-D reconstruction assessments with concordance coefficients for agreement of 0.91 (95% CI: 0.87-0.93) and 0.91 (0.88-0.94) for annulus perimeter and area assessments, respectively. 3-D derived pVD and aVD correlated very closely with a concordance coefficient of 0.97 (0.96-0.98) with a mean difference of 0.5±0.3 mm (pVD-aVD). 3-D derived pVD showed the best, but moderate concordance with diameters obtained from coronal MSCT (0.67, 0.56-0.75; 0.3±1.8 mm), and the lowest concordance with diameters obtained from TEE (0.42, 0.31-0.52; 1.9±1.9 mm). Conclusions: MSCT-based 3-D reconstruction of the aortic annulus using the 3mensio software enables accurate and reproducible assessment of aortic annulus dimensions.

Multicentre validation of the Geneva Risk Score for hospitalised medical patients at risk of venous thromboembolism. Explicit ASsessment of Thromboembolic RIsk and Prophylaxis for Medical PATients in SwitzErland (ESTIMATE).

There is a need to validate risk assessment tools for hospitalised medical patients at risk of venous thromboembolism (VTE). We investigated whether a predefined cut-off of the Geneva Risk Score, as compared to the Padua Prediction Score, accurately distinguishes low-risk from high-risk patients regardless of the use of thromboprophylaxis. In the multicentre, prospective Explicit ASsessment of Thromboembolic RIsk and Prophylaxis for Medical PATients in SwitzErland (ESTIMATE) cohort study, 1,478 hospitalised medical patients were enrolled of whom 637 (43%) did not receive thromboprophylaxis. The primary endpoint was symptomatic VTE or VTE-related death at 90 days. The study is registered at ClinicalTrials.gov, number NCT01277536. According to the Geneva Risk Score, the cumulative rate of the primary endpoint was 3.2% (95% confidence interval [CI] 2.2-4.6%) in 962 high-risk vs 0.6% (95% CI 0.2-1.9%) in 516 low-risk patients (p=0.002); among patients without prophylaxis, this rate was 3.5% vs 0.8% (p=0.029), respectively. In comparison, the Padua Prediction Score yielded a cumulative rate of the primary endpoint of 3.5% (95% CI 2.3-5.3%) in 714 high-risk vs 1.1% (95% CI 0.6-2.3%) in 764 low-risk patients (p=0.002); among patients without prophylaxis, this rate was 3.2% vs 1.5% (p=0.130), respectively. Negative likelihood ratio was 0.28 (95% CI 0.10-0.83) for the Geneva Risk Score and 0.51 (95% CI 0.28-0.93) for the Padua Prediction Score. In conclusion, among hospitalised medical patients, the Geneva Risk Score predicted VTE and VTE-related mortality and compared favourably with the Padua Prediction Score, particularly for its accuracy to identify low-risk patients who do not require thromboprophylaxis.

Food Volume Computation for Self Dietary Assessment Applications

There is great demand for easily-accessible, user-friendly dietary self-management applications. Yet accurate, fully-automatic estimation of nutritional intake using computer vision methods remains an open research problem. One key element of this problem is the volume estimation, which can be computed from 3D models obtained using multi-view geometry. The paper presents a computational system for volume estimation based on the processing of two meal images. A 3D model of the served meal is reconstructed using the acquired images and the volume is computed from the shape. The algorithm was tested on food models (dummy foods) with known volume and on real served food. Volume accuracy was in the order of 90 %, while the total execution time was below 15 seconds per image pair. The proposed system combines simple and computational affordable methods for 3D reconstruction, remained stable throughout the experiments, operates in near real time, and places minimum constraints on users.

The accuracy of self-reported medical history: A preliminary analysis of the promise of internet-based research in Inflammatory Bowel Diseases

BACKGROUND AND AIMS: Internet-based surveys provide a potentially important tool for Inflammatory Bowel Disease (IBD) research. The advantages include low cost, large numbers of participants, rapid study completion and less extensive infrastructure than traditional methods. The aim was to determine the accuracy of patient self-reporting in internet-based IBD research and identify predictors of greater reliability. METHODS: 197 patients from a tertiary care center answered an online survey concerning personal medical history and an evaluation of disease specific knowledge. Self-reported medical details were compared with data abstracted from medical records. Agreement was assessed by kappa (κ) statistics. RESULTS: Participants responded correctly with excellent agreement (κ=0.96-0.97) on subtype of IBD and history of surgery. The agreement was also excellent for colectomy (κ=0.88) and small bowel resection (κ=0.91), moderate for abscesses and fistulas (κ=0.60 and 0.63), but poor regarding partial colectomy (κ=0.39). Time since last colonoscopy was self-reported with better agreement (κ=0.84) than disease activity. For disease location/extent, moderate agreements at κ=69% and 64% were observed for patients with Crohn's disease and ulcerative colitis, respectively. Subjects who scored higher than the average in the IBD knowledge assessment were significantly more accurate about disease location than their complementary group (74% vs. 59%, p=0.02). CONCLUSION: This study demonstrates that IBD patients accurately report their medical history regarding type of disease and surgical procedures. More detailed medical information is less reliably reported. Disease knowledge assessment may help in identifying the most accurate individuals and could therefore serve as validity criteria. Internet-based surveys are feasible with high reliability about basic disease features only. However, the participants in this study were engaged at a tertiary center, which potentially leads to a bias and compromises generalization to an unfiltered patient group.

SwissScoring--a nationwide survey of NEMS assessing practices and its accuracy.

BACKGROUND The nine equivalents of nursing manpower use score (NEMS) is used to evaluate critical care nursing workload and occasionally to define hospital reimbursements. Little is known about the caregivers' accuracy in scoring, about factors affecting this accuracy and how validity of scoring is assured. METHODS Accuracy in NEMS scoring of Swiss critical care nurses was assessed using case vignettes. An online survey was performed to assess training and quality control of NEMS scoring and to collect structural and organizational data of participating intensive care units (ICUs). Aggregated structural and procedural data of the Swiss ICU Minimal Data Set were used for matching. RESULTS Nursing staff from 64 (82%) of the 78 certified adult ICUs participated in this survey. Training and quality control of scoring shows large variability between ICUs. A total of 1378 nurses scored one out of 20 case vignettes: accuracy ranged from 63.7% (intravenous medications) to 99.1% (basic monitoring). Erroneous scoring (8.7% of all items) was more frequent than omitted scoring (3.2%). Mean NEMS per case was 28.0 ± 11.8 points (reference score: 25.7 ± 14.2 points). Mean bias was 2.8 points (95% confidence interval: 1.0-4.7); scores below 37.1 points were generally overestimated. Data from units with a greater nursing management staff showed a higher bias. CONCLUSION Overall, nurses assess the NEMS score within a clinically acceptable range. Lower scores are generally overestimated. Inaccurate assessment was associated with a greater size of the nursing management staff. Swiss head nurses consider themselves motivated to assure appropriate scoring and its validation.

Comparative assessment of ELISAs using recombinant saposin-like protein 2 and recombinant cathepsin L-1 from Fasciola hepatica for the serodiagnosis of human Fasciolosis.

Two recombinant Fasciola hepatica antigens, saposin-like protein-2 (recSAP2) and cathepsin L-1 (recCL1), were assessed individually and in combination in enzyme-linked immunosorbent assays (ELISA) for the specific serodiagnosis of human fasciolosis in areas of low endemicity as encountered in Central Europe. Antibody detection was conducted using ProteinA/ProteinG (PAG) conjugated to alkaline phosphatase. Test characteristics as well as agreement with results from an ELISA using excretory-secretory products (FhES) from adult stage liver flukes was assessed by receiver operator characteristic (ROC) analysis, specificity, sensitivity, Youdens J and overall accuracy. Cross-reactivity was assessed using three different groups of serum samples from healthy individuals (n=20), patients with other parasitic infections (n=87) and patients with malignancies (n=121). The best combined diagnostic results for recombinant antigens were obtained using the recSAP2-ELISA (87% sensitivity, 99% specificity and 97% overall accuracy) employing the threshold (cut-off) to discriminate between positive and negative reactions that maximized Youdens J. The findings showed that recSAP2-ELISA can be used for the routine serodiagnosis of chronic fasciolosis in clinical laboratories; the use of the PAG-conjugate offers the opportunity to employ, for example, rabbit hyperimmune serum for the standardization of positive controls.

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

Peak oxygen uptake test in the assessment of growth hormone deficiency.

This study aimed at evaluating a peak oxygen uptake test as a simple diagnostic tool to assess growth-hormone deficiency (GHD) in adults. Based on the findings of multiple growth hormone (GH) samplings after the exercise, a single GH sample taken 15 min postexercise revealed high accuracy in the diagnosis of GHD in the present study. A standardized peak oxygen uptake test may, therefore, provide an accurate alternative to more invasive tests of GHD.

Achieving a more realistic assessment of rockfall hazards by coupling three-dimensional process models and field-based tree-ring data

Sound knowledge of the spatial and temporal patterns of rockfalls is fundamental for the management of this very common hazard in mountain environments. Process-based, three-dimensional simulation models are nowadays capable of reproducing the spatial distribution of rockfall occurrences with reasonable accuracy through the simulation of numerous individual trajectories on highly-resolved digital terrain models. At the same time, however, simulation models typically fail to quantify the ‘real’ frequency of rockfalls (in terms of return intervals). The analysis of impact scars on trees, in contrast, yields real rockfall frequencies, but trees may not be present at the location of interest and rare trajectories may not necessarily be captured due to the limited age of forest stands. In this article, we demonstrate that the coupling of modeling with tree-ring techniques may overcome the limitations inherent to both approaches. Based on the analysis of 64 cells (40 m × 40 m) of a rockfall slope located above a 1631-m long road section in the Swiss Alps, we illustrate results from 488 rockfalls detected in 1260 trees. We illustrate that tree impact data cannot only be used (i) to reconstruct the real frequency of rockfalls for individual cells, but that they also serve (ii) the calibration of the rockfall model Rockyfor3D, as well as (iii) the transformation of simulated trajectories into real frequencies. Calibrated simulation results are in good agreement with real rockfall frequencies and exhibit significant differences in rockfall activity between the cells (zones) along the road section. Real frequencies, expressed as rock passages per meter road section, also enable quantification and direct comparison of the hazard potential between the zones. The contribution provides an approach for hazard zoning procedures that complements traditional methods with a quantification of rockfall frequencies in terms of return intervals through a systematic inclusion of impact records in trees.

At risk or not at risk? A meta-analysis of the prognostic accuracy of psychometric interviews for psychosis prediction

An accurate detection of individuals at clinical high risk (CHR) for psychosis is a prerequisite for effective preventive interventions. Several psychometric interviews are available, but their prognostic accuracy is unknown. We conducted a prognostic accuracy meta-analysis of psychometric interviews used to examine referrals to high risk services. The index test was an established CHR psychometric instrument used to identify subjects with and without CHR (CHR+ and CHR-). The reference index was psychosis onset over time in both CHR+ and CHR- subjects. Data were analyzed with MIDAS (STATA13). Area under the curve (AUC), summary receiver operating characteristic curves, quality assessment, likelihood ratios, Fagan's nomogram and probability modified plots were computed. Eleven independent studies were included, with a total of 2,519 help-seeking, predominately adult subjects (CHR+: N=1,359; CHR-: N=1,160) referred to high risk services. The mean follow-up duration was 38 months. The AUC was excellent (0.90; 95% CI: 0.87-0.93), and comparable to other tests in preventive medicine, suggesting clinical utility in subjects referred to high risk services. Meta-regression analyses revealed an effect for exposure to antipsychotics and no effects for type of instrument, age, gender, follow-up time, sample size, quality assessment, proportion of CHR+ subjects in the total sample. Fagan's nomogram indicated a low positive predictive value (5.74%) in the general non-help-seeking population. Albeit the clear need to further improve prediction of psychosis, these findings support the use of psychometric prognostic interviews for CHR as clinical tools for an indicated prevention in subjects seeking help at high risk services worldwide.

Accuracy of cartilage-specific 3-Tesla 3D-DESS magnetic resonance imaging in the diagnosis of chondral lesions: comparison with knee arthroscopy

BACKGROUND Arthroscopy is considered as "the gold standard" for the diagnosis of traumatic intraarticular knee lesions. However, recent developments in magnetic resonance imaging (MRI) now offer good opportunities for the indirect assessment of the integrity and structural changes of the knee articular cartilage. The study was to investigate whether cartilage-specific sequences on a 3-Tesla MRI provide accurate assessment for the detection of cartilage defects. METHODS A 3-Tesla (3-T) MRI combined with three-dimensional double-echo steady-state (3D-DESS) cartilage specific sequences was performed on 210 patients with knee pain prior to knee arthroscopy. Sensitivity, specificity, and positive and negative predictive values of magnetic resonance imaging were calculated and correlated to the arthroscopic findings of cartilaginous lesions. Lesions were classified using the modified Outerbridge classification. RESULTS For the 210 patients (1260 cartilage surfaces: patella, trochlea, medial femoral condyle, medial tibia, lateral femoral condyle, lateral tibia) evaluated, the sensitivities, specificities, positive predictive values, and negative predictive values of 3-T MRI were 83.3, 99.8, 84.4, and 99.8 %, respectively, for the detection of grade IV lesions; 74.1, 99.6, 85.2, and 99.3 %, respectively, for grade III lesions; 67.9, 99.2, 76.6, and 98.2 %, respectively, for grade II lesions; and 8.8, 99.5, 80, and 92 %, respectively, for grade I lesions. CONCLUSIONS For grade III and IV lesions, 3-T MRI combined with 3D-DESS cartilage-specific sequences represents an accurate diagnostic tool. For grade II lesions, the technique demonstrates moderate sensitivity, while for grade I lesions, the sensitivity is limited to provide reliable diagnosis compared to knee arthroscopy.

Thrombus formation in the left ventricle after large myocardial infarction – assessment with cardiac magnetic resonance imaging

INTRODUCTION Left ventricular thrombus (LVT) formation may worsen the post-infarct outcome as a result of thromboembolic events. It also complicates the use of modern antiplatelet regimens, which are not compatible with long-term oral anticoagulation. The knowledge of the incidence of LVT may therefore be of importance to guide antiplatelet and antithrombotic therapy after acute myocardial infarction (AMI). METHODS In 177 patients with large, mainly anterior AMI, standard cardiac magnetic resonance imaging (CMR) including cine and late gadolinium enhancement (LGE) imaging was performed shortly after AMI as per protocol. CMR images were analysed at an independent core laboratory blinded to the clinical data. Transthoracic echocardiography (TTE) was not mandatory for the trial, but was performed in 64% of the cases following standard of care. In a logistic model, 3 out of 61 parameters were used in a multivariable model to predict LVT. RESULTS LVT was detected by use of CMR in 6.2% (95% confidence interval [CI] 3.1%-10.8%). LGE sequences were best to detect LVT, which may be missed in cine sequences. We identified body mass index (odds ratio 1.18; p = 0.01), baseline platelet count (odds ratio 1.01, p = 0.01) and infarct size as assessed by use of CMR (odds ratio 1.03, p = 0.02) as best predictors for LVT. The agreement between TTE and CMR for the detection of LVT is substantial (kappa = 0.70). DISCUSSION In the current analysis, the incidence of LVT shortly after AMI is relatively low, even in a patient population at high risk. An optimal modality for LVT detection is LGE-CMR but TTE has an acceptable accuracy when LGE-CMR is not available.

Accuracy of conventional radiography and computed tomography in predicting implant position in relation to the vertebral canal in dogs.

OBJECTIVE To compare the accuracy of radiography and computed tomography (CT) in predicting implant position in relation to the vertebral canal in the cervical and thoracolumbar vertebral column. STUDY DESIGN In vitro imaging and anatomic study. ANIMALS Medium-sized canine cadaver vertebral columns (n=12). METHODS Steinmann pins were inserted into cervical and thoracolumbar vertebrae based on established landmarks but without predetermination of vertebral canal violation. Radiographs and CT images were obtained and evaluated by 6 individuals. A random subset of pins was evaluated for ability to distinguish left from right pins on radiographs. The ability to correctly identify vertebral canal penetration for all pins was assessed both on radiographs and CT. Spines were then anatomically prepared and visual examination of pin penetration into the canal served as the gold standard. RESULTS Left/right accuracy was 93.1%. Overall sensitivity of radiographs and CT to detect vertebral canal penetration by an implant were significantly different and estimated as 50.7% and 93.4%, respectively (P<.0001). Sensitivity was significantly higher for complete versus partial penetration and for radiologists compared with nonradiologists for both imaging modalities. Overall specificity of radiographs and CT to detect vertebral canal penetration was 82.9% and 86.4%, respectively (P=.049). CONCLUSIONS CT was superior to radiographic assessment and is the recommended imaging modality to assess penetration into the vertebral canal. CLINICAL RELEVANCE CT is significantly more accurate in identifying vertebral canal violation by Steinmann pins and should be performed postoperatively to assess implant position.

Dish Detection and Segmentation for Dietary Assessment on Smartphones

Diet-related chronic diseases severely affect personal and global health. However, managing or treating these diseases currently requires long training and high personal involvement to succeed. Computer vision systems could assist with the assessment of diet by detecting and recognizing different foods and their portions in images. We propose novel methods for detecting a dish in an image and segmenting its contents with and without user interaction. All methods were evaluated on a database of over 1600 manually annotated images. The dish detection scored an average of 99% accuracy with a .2s/image run time, while the automatic and semi-automatic dish segmentation methods reached average accuracies of 88% and 91% respectively, with an average run time of .5s/image, outperforming competing solutions.