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Objective: To determine the level of agreement of disease flare severity (distinguishing severe, moderate, and mild flare and persistent disease activity) in a large paper-patient exercise involving 988 individual cases of systemic lupus erythematosus.Methods: A total of 988 individual lupus case histories were assessed by 3 individual physicians. Complete agreement about the degree of flare (or persistent disease activity) was obtained in 451 cases (46%), and these provided the reference standard for the second part of the study. This component used 3 flare activity instruments (the British Isles Lupus Assessment Group [BILAG] 2004, Safety of Estrogens in Lupus Erythematosus National Assessment [SELENA] flare index [SFI] and the revised SELENA flare index [rSFI]). The 451 patient case histories were distributed to 18 pairs of physicians, carefully randomized in a manner designed to ensure a fair case mix and equal distribution of flare according to severity.Results: The 3-physician assessment of flare matched the level of flare using the 3 indices, with 67% for BILAG 2004, 72% for SFI, and 70% for rSFI. The corresponding weighted kappa coefficients for each instrument were 0.82, 0.59, and 0.74, respectively. We undertook a detailed analysis of the discrepant cases and several factors emerged, including a tendency to score moderate flares as severe and persistent activity as flare, especially when the SFI and rSFI instruments were used. Overscoring was also driven by scoring treatment change as flare, even if there were no new or worsening clinical features.Conclusion: Given the complexity of assessing lupus flare, we were encouraged by the overall results reported. However, the problem of capturing lupus flare accurately is not completely solved. [ABSTRACT FROM AUTHOR]

Objectives: A new patient-reported outcome (PRO) instrument to measure fatigue symptoms and impacts in relapsing multiple sclerosis (RMS) was developed in a qualitative stage, followed by psychometric validation and migration from paper to an electronic format.Methods: Adult patients with relapsing-remitting multiple sclerosis (RRMS) were interviewed to elicit fatigue-related symptoms and impacts. A draft questionnaire was debriefed in cognitive interviews with further RRMS patients, and revised. Content confirmation interviews were conducted with patients with progressive-relapsing multiple sclerosis (PRMS) and relapsing secondary-progressive multiple sclerosis (RSPMS). Psychometric analyses used data from adult patients with different RMS subtypes and matched non-RMS controls in a multicenter, observational study. After item reduction, the final instrument was migrated to a smartphone (eDiary) and usability was confirmed in interviews with additional adult RMS patients.Results: The qualitative stage included 37 RRMS, 5 PRMS, and 5 RSPMS patients. Saturation of concepts was reached during concept elicitation. Cognitive interviews confirmed that participants understood the instructions, items, and response options of the instrument-named FSIQ-RMS-as intended. Psychometric validation included 164 RMS and 74 control patients. Internal consistency and test-retest reliability were demonstrated. The symptoms domain discriminated along the RMS symptom-severity continuum and between patients and controls. Patients were able to attribute fatigue-related symptoms to RMS. Usability and conceptual equivalence of the eDiary were confirmed (n = 10 participants).Conclusions: With 7 symptom items and 13 impact items (in 3 impacts subdomains: physical, cognitive and emotional, and coping) after item reduction, the FSIQ-RMS is a comprehensive, valid, and reliable measure of fatigue-related symptoms and impacts in RMS patients. [ABSTRACT FROM AUTHOR]

Aim: To assess the reliability and predictive validity of the developmental and socio-emotional scales of the Standardized Infant NeuroDevelopmental Assessment (SINDA).Method: To assess reliability, two sets of three assessors forming eight assessor-pairs independently rated the developmental and socio-emotional scales of 60 infants. To evaluate predictive validity, 223 infants (gestational age 30wks [range 23-41wks]; 117 males, 106 females) attending a non-academic outpatient clinic were assessed by different assessors with SINDA's neurological, developmental, and socio-emotional scales. Atypical neurodevelopmental outcome at a corrected age of 24 months or older implied a Bayley Mental or Psychomotor Developmental Index score of less than 70 or neurological disorder (including cerebral palsy). Behavioural and emotional disorders were classified according to the International Classification of Diseases, 10th Revision. Predictive values were calculated from SINDA (2-12mo corrected age, median 7mo) and typical versus atypical outcome, and for intellectual disability only (Mental Developmental Index <70).Results: Assessors highly agreed on the developmental and socio-emotional assessments (developmental scores: Spearman's rank correlation coefficient ρ=0.972; single socio-emotional behaviour items: Cohen's κ=0.783-0.896). At 24 months or older, 65 children had atypical outcome. Atypical neurological scores predicted atypical outcome (sensitivity 83%, specificity 96%); atypical developmental scores predicted intellectual disability (sensitivity 77%, specificity 92%). Atypical emotionality and atypical self-regulation were associated with behavioural and emotional disorders.Interpretation: SINDA's three scales are reliable, and have a satisfactory predictive validity for atypical developmental outcome at 24 months or older in a non-academic outpatient setting. SINDA's developmental scale has promising predictive validity for intellectual disability. SINDA's socio-emotional scale is a tool for caregiver counselling.What This Paper Adds: Standardized Infant NeuroDevelopmental Assessment (SINDA)'s developmental and socio-emotional scales have excellent interrater reliability. Replication of the satisfactory validity of SINDA's neurological scale for atypical outcome. [ABSTRACT FROM AUTHOR]

Background: Free and Cued Selective Reminding Test (FCSRT) is a reliable cognitive marker for Alzheimer's disease (AD), and the identification of neuropsychological tests sensitive to the early signs of AD pathology is crucial both in research and clinical practice.Objective: The study aimed to ascertain the ability of FCSRT in predicting the amyloid load as determined from amyloid PET imaging (Amy-PET) in patients with cognitive disorders.Methods: For our purpose, 79 patients (71 MCI, 8 mild dementia) underwent a complete workup for dementia, including the FCSRT assessment and a [18F]florbetaben PET scan. FCSRT subitem scores were used as predictors in different binomial regression models.Results: Immediate free recall and delayed free recall were the best predictors overall in the whole sample; whereas in patients <76 years, all models further improved with immediate total recall (ITR) and Index of Sensitivity of Cueing (ISC) resulting the most accurate in anticipating Amy-PET results, with a likelihood of being Amy-PET positive greater than 85% for ITR and ISC scores of less than 25 and 0.5, respectively.Conclusion: FCSRT proved itself to be a valid tool in dementia diagnosis, also being able to correlate with amyloid pathology. The possibility to predict Amy-PET results through a simple and reliable neuropsychological test might be helpful for clinicians in the dementia field, adding value to a paper and pencil tool compared to most costly biomarkers. [ABSTRACT FROM AUTHOR]

For patients with major burn injuries, an accurate burn size estimation is essential to plan appropriate treatment and minimize medical and surgical complications. However, current clinical methods for burn size estimation lack accuracy and reliability. To overcome these limitations, this paper proposes a 3D-based approach-with personalized 3D models from a limited set of anthropometric measurements-to accurately assess the percent TBSA affected by burns. First, a reliability and feasibility study of the anthropometric measuring process was performed to identify clinically relevant measurements. Second, a large representative stratified random sample was generated to output several anthropometric features required for predictive modeling. Machine-learning algorithms assessed the importance and the subsets of anthropometric measurements for predicting the BSA according to specific patient morphological features. Then, the accuracy of both the morphology and BSA of 3D models built from a limited set of measurements was evaluated using error metrics and maximum distances 3D color maps. Results highlighted the height and circumferences of the bust, neck, hips, and waist as the best predictors for BSA. 3D models built from three to four anthropometric measurements showed good accuracy and were geometrically close to gold standard 3D scans. Outcomes of this study aim to decrease medical and surgical complications by decreasing errors in percent TBSA assessments and, therefore, improving patient outcomes by personalizing care. [ABSTRACT FROM AUTHOR]

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The present paper has three objectives. First, methods for comparing alternative tests for the purpose of replacement of one test with a second presumably superior test are described. Second, problems in the interpretation of the relevance of different diagnostic thresholds (thresholds of positivity) that define who is and who is not a disordered gambler are examined and a potential solution offered in the form of a common quantitative measure of the risk of being a disordered gambler. Third, alternative methodologies are described as potential solutions to the lack of a gold or reference standard in the evaluation of new tests. [ABSTRACT FROM AUTHOR]

Background: This paper explores the importance of electronic medical records (EMR) for predicting 30-day all-cause non-elective readmission risk of patients and presents a comparison of prediction performance of commonly used methods.Methods: The data are extracted from eight Advocate Health Care hospitals. Index admissions are excluded from the cohort if they are observation, inpatient admissions for psychiatry, skilled nursing, hospice, rehabilitation, maternal and newborn visits, or if the patient expires during the index admission. Data are randomly and repeatedly divided into fitting and validating sets for cross validations. Approaches including LACE, STEPWISE logistic, LASSO logistic, and AdaBoost, are compared with sample sizes varying from 2,500 to 80,000.Results: Our results confirm that LACE has moderate discrimination power with the area under receiver operating characteristic curve (AUC) around 0.65-0.66, which can be improved to 0.73-0.74 when additional variables from EMR are considered. These variables include Inpatient in the last six months, Number of emergency room visits or inpatients in the last year, Braden score, Polypharmacy, Employment status, Discharge disposition, Albumin level, and medical condition variables such as Leukemia, Malignancy, Renal failure with hemodialysis, History of alcohol substance abuse, Dementia and Trauma. When sample size is small (≤5000), LASSO is the best; when sample size is large (≥20,000), the predictive performance is similar. The STEPWISE method has a slightly lower AUC (0.734) comparing to LASSO (0.737) and AdaBoost (0.737). More than one half of the selected predictors can be false positives when using a single method and a single division of fitting/validating data.Conclusions: True predictors can be identified by repeatedly dividing data into fitting/validating subsets and referring the final model based on summarizing results. LASSO is a better alternative to the STEPWISE logistic regression, especially when sample size is not large. The evidence for adequate sample size can be explored by fitting models on gradually reduced samples. Our model comparison strategy is not only good for 30-day all-cause non-elective readmission risk predictions, but also applicable to other types of predictive models in clinical studies. [ABSTRACT FROM AUTHOR]

Objectives: This paper is aimed to explore the value of double source CT angiography (DS-CTA) for diagnosing in-stent restenosis in lower limb artery.Methods: From January 2016 to October 2018, all patients with stent in lower limb artery in our hospital were investigated by both DS-CTA and digital subtraction angiography. We measured the minimum lumen diameter and the diameter of the proximal normal vessels under each stent placement. The in-stent restenosis is defined as restenosis when the lumen area decreased by more than 50%. Digital subtraction angiography was performed within 1 week after DS-CT scan. Relationship between DS-CTA and digital subtraction angiography for diagnosing in-stent restenosis in lower limb artery was analyzed. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of DS-CTA for diagnosis of in-stent restenosis were analyzed with digital subtraction angiography as the reference standard. A total of 68 stents were placed in 51 patients. Among these patients, 27 cases were diagnosed as in-stent restenosis, presenting as endovascular contrast agent bias or crescent filling defect with the lumen area reducing over 50%, 6 cases of which had no significant in-stent restenosis by digital subtraction angiography analysis. Furthermore, 12 cases were occlusion, in which there was no high density contrast agent in stents; the remaining 41 stents were unobstructed and the contrast agent was filled well, 8 cases of which had significant in-stent restenosis by digital subtraction angiography analysis. In addition, four stents were deformed or distorted. Statistical analysis demonstrated the concentrations of DS-CTA and digital subtraction angiography in diagnosing in-stent restenosis for lower limb artery were closely related, and the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of DS-CTA were 72.4%, 84.6%, 77.8%, 80.5%, and 79.4%, respectively.Conclusion: DS-CTA has a potential reliability for diagnosis of in-stent restenosis in lower limb artery, which may be further improved to be used for clinical interventional treatment of vascular diseases. [ABSTRACT FROM AUTHOR]

Fluid-solid interaction is a primary feature of cardiovascular flows. There is increasing interest in the numerical solution of these systems as the extensive computational resource required for such studies becomes available. One form of coupling is an external weak coupling of separate solid and fluid mechanics codes. Information about the stress tensor and displacement vector at the wetted boundary is passed between the codes, and an iterative scheme is employed to move towards convergence of these parameters at each time step. This approach has the attraction that separate codes with the most extensive functionality for each of the separate phases can be selected, which might be important in the context of the complex rheology and contact mechanics that often feature in cardiovascular systems. Penrose and Staples describe a weak coupling of CFX for computational fluid mechanics to ANSYS for solid mechanics, based on a simple Jacobi iteration scheme. It is important to validate the coupled numerical solutions. An extensive analytical study of flow in elastic-walled tubes was carried out by Womersley in the late 1950s. This paper describes the performance of the coupling software for the straight elastic-walled tube, and compares the results with Womersley's analytical solutions. It also presents preliminary results demonstrating the application of the coupled software in the context of a stented vessel. [ABSTRACT FROM AUTHOR]

The brain connections in the different regions demonstrate the characteristics of brain activities. In addition, in various conditions and with neuropsychological disorders, the brain has special patterns in different regions. This paper presents a model to show and compare the connection patterns in different brain regions of children with autism (53 boys and 36 girls) and control children (61 boys and 33 girls). The model is designed by cellular neural networks and it uses the proper features of electroencephalography. The results show that there are significant differences and abnormalities in the left hemisphere, (p < 0.05) at the electrodes AF3, F3, P7, T7, and O1 in the children with autism compared with the control group. Also, the evaluation of the obtained connections values between brain regions demonstrated that there are more abnormalities in the connectivity of frontal and parietal lobes and the relations of the neighboring regions in children with autism. It is observed that the proposed model is able to distinguish the autistic children from the control subjects with an accuracy rate of 95.1% based on the obtained values of CNN using the SVM method. [ABSTRACT FROM AUTHOR]

Diagnostic information regarding the health status of the corneal endothelium may be obtained by analyzing the size and the shape of the endothelial cells in specular microscopy images. Prior to the analysis, the endothelial cells need to be extracted from the image. Up to today, this has been performed manually or semi-automatically. Several approaches to automatic segmentation of endothelial cells exist; however, none of them is perfect. Therefore this paper proposes to perform cell segmentation using a U-Net-based convolutional neural network. Particularly, the network is trained to discriminate pixels located at the borders between cells. The edge probability map outputted by the network is next binarized and skeletonized in order to obtain one-pixel wide edges. The proposed solution was tested on a dataset consisting of 30 corneal endothelial images presenting cells of different sizes, achieving an AUROC level of 0.92. The resulting DICE is on average equal to 0.86, which is a good result, regarding the thickness of the compared edges. The corresponding mean absolute percentage error of cell number is at the level of 4.5% which confirms the high accuracy of the proposed approach. The resulting cell edges are well aligned to the ground truths and require a limited number of manual corrections. This also results in accurate values of the cell morphometric parameters. The corresponding errors range from 5.2% for endothelial cell density, through 6.2% for cell hexagonality to 11.93% for the coefficient of variation of the cell size. [ABSTRACT FROM AUTHOR]

Lung sounds convey relevant information related to pulmonary disorders, and to evaluate patients with pulmonary conditions, the physician or the doctor uses the traditional auscultation technique. However, this technique suffers from limitations. For example, if the physician is not well trained, this may lead to a wrong diagnosis. Moreover, lung sounds are non-stationary, complicating the tasks of analysis, recognition, and distinction. This is why developing automatic recognition systems can help to deal with these limitations. In this paper, we compare three machine learning approaches for lung sounds classification. The first two approaches are based on the extraction of a set of handcrafted features trained by three different classifiers (support vector machines, k-nearest neighbor, and Gaussian mixture models) while the third approach is based on the design of convolutional neural networks (CNN). In the first approach, we extracted the 12 MFCC coefficients from the audio files then calculated six MFCCs statistics. We also experimented normalization using zero mean and unity variance to enhance accuracy. In the second approach, the local binary pattern (LBP) features are extracted from the visual representation of the audio files (spectrograms). The features are normalized using whitening. The dataset used in this work consists of seven classes (normal, coarse crackle, fine crackle, monophonic wheeze, polyphonic wheeze, squawk, and stridor). We have also experimentally tested dataset augmentation techniques on the spectrograms to enhance the ultimate accuracy of the CNN. The results show that CNN outperformed the handcrafted feature based classifiers. [ABSTRACT FROM AUTHOR]

Several authors have suggested that dementia screening tests may be biased against low levels of education, whereas others find that a low level of education is a genuine risk factor for dementia. The present paper attempts to reconcile these conflicting views by examining item bias and test bias indices of the mini mental state examination (MMSE). Psychometric calculations and receiver operating characteristics (ROC) analyses of sensitivity and specificity as performed by earlier studies were replicated and extended from the database of the Amsterdam Study of the Elderly. This is a population survey on cognitive decline and dementia (age range 65-84). Subjects with a low level of education (primary school) were compared with better educated subjects (at least some secondary education). Cases were matched by age and sex. The results indicate that the MMSE is not educationally biased as far as item characteristics, reliability, and construct validity are concerned. Yet its predictive validity as a screening test for dementia is educationally biased. This bias will effectively be eliminated with a two point higher cut off score for the subjects whose education extends beyond primary school. Even after such score correction, a low level of education probably remains a genuine risk factor for dementia. [ABSTRACT FROM AUTHOR]

The Epidemiological Catchment Area (ECA) program is a major step in psychiatric epidemiology because it uses a structured interview: the Diagnostic Interview Schedule (DIS). This gives psychiatric diagnoses in different diagnostic systems and can be administered by lay interviewers. However many surveys on health-related topics cannot give the time needed to administer the DIS and train the personnel to use such a complex schedule as the DIS. The DISSA is a self-administered abridged form of the DIS and represents an effort to produce a short and simple instrument for three types of diagnoses: major depressive disorder, all anxiety disorders (generalized anxiety, phobias, panic) and alcohol disorders. In this paper we describe the DISSA and give preliminary evidence about its efficiency. This will be done by comparing DISSA results with clinicians judgments, the DIS and a checklist derived from HSC. The DISSA functions in a manner similar to its parent instrument but achieves this in a shorter and less costly mode. Actually the approach by episode used for assessing depression seems to work better than the DIS. Comparisons with the checklist show a clear superiority of the DISSA for depression, alcohol and anxiety disorders but not for generalized anxiety. [ABSTRACT FROM AUTHOR]

Current international attention to Health in all policies (HiAP) has its origins in a more sophisticated understanding of the impact of public policies on health, and a recognition that policies across government have an impact on the social and environmental determinants of health and related inequalities in health. As an emerging field, there has been limited attention focused on comprehensive approaches to the evaluation of HiAP to date, and the research focus around HiAP has mainly examined the processes of cross-sectoral policy development, rather than their health-related impacts or outcomes. The purpose of this paper is to explore issues in assessing the implementation of HiAP and describe an expanded evaluation framework for assessing the potential intermediate and end-point effects of HiAP actions, using a planning logic model for ‘complex programs’. This meets the needs of public sector policy-makers who express an interest in understanding the relationship between HiAP and health-related and social outcomes. The paper proposes applying a contribution analysis method to estimate and model the anticipated impacts of HiAP policies on intermediate and longer term outcomes, in advance of empirical studies of these outcomes, and as an innovative input into HiAP and evaluation planning. A broader long-term evaluation framework will enhance the political saliency of HiAP initiatives, especially from governments considering HiAP approaches in financially constrained environments. [ABSTRACT FROM PUBLISHER]

Background: Multistep immunoassay kits for the diagnosis of rupture of membranes are relatively complex and are not designed to be used by pregnant women themselves. These kits require procedural steps of specimen extraction and preparation. We evaluated the ability of a sanitary pad containing a qualitative immunoassay for alpha-fetoprotein (AFP) to serve as a one-step self-test to detect amniotic fluid leakage.Technique: Four sets of pads were evaluated. The pads in the study set were worn by 288 pregnant women with confirmed rupture of membranes. Three controls were evaluated: 1) pads worn by 93 pregnant women with intact membranes, 2) additional pads instilled with urine specimens obtained from the 381 women described previously (study set plus control set 1), and 3) pads instilled with semen collected from 40 men.Experience: All 288 pads that absorbed amniotic fluid had positive results. Approximately half of the pads absorbed with normal vaginal discharge had a sufficient amount to yield valid results, which were all negative. All 381 pads with instilled urine and all 40 pads with instilled semen had negative results.Conclusion: An immunoassay for AFP, embedded in a pad, appears to be a feasible and reproducible self-test for the detection of rupture of membranes. [ABSTRACT FROM AUTHOR]

Background: The outcomes of psychological therapies for anxiety and depression vary across individuals and symptom domains. Being able to predict treatment response from readily available patient data at presentation has potentially important benefits in aiding decisions about the most suitable interventions for a patient. This paper presents a method of identifying subgroups of patients using latent profile analysis, and comparing response to psychological treatments between these profiles.Methods: All outpatients taken into treatment at two psychological treatment services in London, UK and who provided basic demographic information and standardized symptom measures were included in the analysis (n=16636).Results: Latent Profile Analysis was performed on intake data to identify statistically different groups of patients, which were then examined in longitudinal analyses to determine their capacity to predict treatment outcomes. Comparison between profiles showed considerable variation in recovery (74-15%), deterioration rates (5-20%), and levels of attrition (17-40%). Further variation in outcomes was found within the profiles when different intensities of psychological intervention were delivered.Limitations: Latent profiles were identified using data from two services, so generalisability to other services should be considered. Routinely collected patient data was included, additional patient information may further enhance utility of the profiles.Conclusions: These results suggest that intake data can be used to reliably classify patients into profiles that are predictive of outcome to different intensities of psychological treatment in routine care. Algorithms based on these kinds of data could be used to optimize decision-making and aid the appropriate matching of patients to treatment. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the performance of a new electronic screening tool (TARB-Ex) in detecting general practice patients at potential risk of familial hypercholesterolaemia (FH).Methods: Medical records for all active patients seen between 2012 and 2014 (n=3708) at a large general practice in Perth, Western Australia were retrospectively screened for potential FH risk using TARB-Ex. Electronic extracts of medical records for patients identified with potential FH risk (defined as Dutch Lipid Clinic Network Criteria (DLCNC) score ≥5) through TARB-Ex were reviewed by a general practitioner (GP) and lipid specialist. High-risk patients were recalled for clinical assessment to determine phenotypic FH diagnosis. Performance was evaluated against a manual record review by a GP in the subset of 360 patients with high blood cholesterol (cholesterol ≥7 mmol/L or low-density lipoprotein cholesterol ≥4.0 mmol/L).Results: Thirty-two patients with DLCNC score ≥5 were identified through electronic screening compared with 22 through GP manual review. Sensitivity was 95.5% (95% CI 77.2% to 99.9%), specificity was 96.7% (95% CI 94.3% to 98.3%), negative predictive accuracy was 99.7% (95% CI 98.3% to 100%) and positive predictive accuracy was 65.6% (95% CI 46.9% to 8%). Electronic screening was completed in 10 min compared with 60 h for GP manual review. 10 of 32 patients (31%) were considered high risk and recalled for clinical assessment. Six of seven patients (86%) who attended clinical assessment were diagnosed with phenotypic FH on examination.Conclusions: TARB-Ex screening is a time-effective and cost-effective method of systematically identifying potential FH risk patients from general practice records for clinical follow-up. [ABSTRACT FROM AUTHOR]

Objective: This paper aims at developing an automated gastroscopic video summarization algorithm to assist clinicians to more effectively go through the abnormal contents of the video.Methods and Materials: To select the most representative frames from the original video sequence, we formulate the problem of gastroscopic video summarization as a dictionary selection issue. Different from the traditional dictionary selection methods, which take into account only the number and reconstruction ability of selected key frames, our model introduces the similar-inhibition constraint to reinforce the diversity of selected key frames. We calculate the attention cost by merging both gaze and content change into a prior cue to help select the frames with more high-level semantic information. Moreover, we adopt an image quality evaluation process to eliminate the interference of the poor quality images and a segmentation process to reduce the computational complexity.Results: For experiments, we build a new gastroscopic video dataset captured from 30 volunteers with more than 400k images and compare our method with the state-of-the-arts using the content consistency, index consistency and content-index consistency with the ground truth. Compared with all competitors, our method obtains the best results in 23 of 30 videos evaluated based on content consistency, 24 of 30 videos evaluated based on index consistency and all videos evaluated based on content-index consistency.Conclusions: For gastroscopic video summarization, we propose an automated annotation method via similar-inhibition dictionary selection. Our model can achieve better performance compared with other state-of-the-art models and supplies more suitable key frames for diagnosis. The developed algorithm can be automatically adapted to various real applications, such as the training of young clinicians, computer-aided diagnosis or medical report generation. [ABSTRACT FROM AUTHOR]

Objective: A model that can predict reliably the risk of pre-eclampsia (PE)-related pregnancy complications does not exist. The aim of this study was to develop and validate internally a clinical prediction model to predict the risk of a composite outcome of PE-related maternal and fetal complications within 7, 14 and 30 days of testing in women with suspected or confirmed PE.Methods: The data for this study were derived from a prospective, multicenter, observational cohort study on women with a singleton pregnancy and suspected or confirmed PE at 20 to < 37 weeks' gestation. For the development of the prediction model, the possible contribution of clinical and standard laboratory variables, as well as the biomarkers soluble fms-like tyrosine kinase-1 (sFlt-1), placental growth factor (PlGF) and their ratio, in the prediction of a composite outcome of PE-related complications, consisting of maternal and fetal adverse events within 7, 14 and 30 days, was explored using multivariable competing-risks regression analysis. The discriminative ability of the model was assessed using the concordance (c-) statistic. A bootstrap validation procedure with 500 replications was used to correct the estimate of the prediction model performance for optimism and to compute a shrinkage factor for the regression coefficients to correct for overfitting.Results: Among 384 women with suspected or confirmed PE, 96 (25%) had an adverse PE-related outcome at any time after hospital admission. Important predictors of adverse PE-related outcome included sFlt-1/PlGF ratio, gestational age at the time of biomarker measurement and protein-to-creatinine ratio as continuous variables. The c-statistics (corrected for optimism) for developing a PE-related complication within 7, 14 and 30 days were 0.89, 0.88 and 0.87, respectively. There was limited overfitting, as indicated by a shrinkage factor of 0.91.Conclusions: We propose a simple clinical prediction model with good discriminative performance to predict PE-related complications. Determination of its usefulness in clinical practice awaits further investigation and external validation. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

Background: Kessler's Psychological Distress Scale (K10) is a ten-item measure of psychological distress that has been used in recent epidemiological research and as a screen for mental disorders. Moderate relationships have been reported between the K10 and measures of related constructs, such as diagnoses of mental disorders and associated disability. However, it is unclear whether the validity of the K10 is consistent across important demographic, cultural, and socio-economic groups such as gender and educational history or whether there is evidence of predictive bias or inconsistency across these groups.Methods: Differential validity or predictive bias in the relationship between K10 scores and disability days, SF12 Mental Component Summary (MCS) scores, and 1-month Composite International Diagnostic Interview (CIDI) diagnoses of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) Anxiety and Depressive disorders due to gender and completing secondary school were examined using hierarchical linear and logistic regression analyses in the Australian National Survey of Mental Health and Wellbeing data set.Results: Very small slope and/or intercept biases in the relationship between the K10 and disability days, the SF12 MCS, and 1-month CIDI diagnoses of anxiety and depression were found [effect sizes, the ratio of variance explained to unexplained variance (Cohen's f2), varied from 0.0001 to 0.004].Conclusion: Gender and educational predictive biases in the relationship between the K10 and disability days, SF12 MCS, and 1-month diagnoses were found to be very small and are unlikely to have any practical impact. This analysis adds to evidence supporting the use of the K10 in epidemiological research. [ABSTRACT FROM AUTHOR]

With rapid development in the technology of measuring disease characteristics at molecular or genetic level, it is possible to collect a large amount of data on various potential predictors of the clinical outcome of interest in medical research. It is often of interest to effectively use the information on a large number of predictors to make prediction of the interested outcome. Various statistical tools were developed to overcome the difficulties caused by the high-dimensionality of the covariate space in the setting of a linear regression model. This paper focuses on the situation, where the interested outcomes are subjected to right censoring. We implemented the extended partial least squares method along with other commonly used approaches for analyzing the high-dimensional covariates to the ACTG333 data set. Especially, we compared the prediction performance of different approaches with extensive cross-validation studies. The results show that the Buckley-James based partial least squares, stepwise subset model selection and principal components regression have similar promising predictive power and the partial least square method has several advantages in terms of interpretability and numerical computation. [ABSTRACT FROM AUTHOR]

Background: Early recurrences of atrial arrhythmias (ERAA) after atrial fibrillation (AF) catheter ablation do not predict procedural failure. A well-demarcated homogeneous lesion delivered by cryoballoon is less arrhythmogenic, and the recommended three-months blanking period may not refer to cryoballoon ablation (CBA).Objective: We aimed to evaluate the predictive role of ERAA after second-generation CBA using an implantable loop recorder.Methods: This prospective observational study enrolled 100 patients (58 males, median age 58) with paroxysmal/persistent AF undergoing pulmonary vein (PV) CBA using second-generation cryoballoon with simultaneous ECG loop recorder implantation. The duration of follow-up was 12 months, with scheduled visits at 3, 6 and 12 months.Results: 99 patients from 100 completed the 12-month follow-up period. ERAA occurred in 31.3 % of patients. 83.9 % of patients with ERAA also developed late recurrences. The 12-month freedom from AF in patients with ERAA was significantly lower than in those without ERAA (p < 0.0001). Non-paroxysmal AF and longer arrhythmia history were associated with increased risk of both early (HR 3.27; 95 % CI 1.32-8.08; p = 0.010 and HR 1.0147; 95 % CI 1.008-1.086; p = 0.015, respectively) and late recurrences (HR 3.89; 95 % CI 1.67-9.04; p = 0.002 and HR 1.0142; 95 % CI 1.007-1.078; p = 0.019, respectively) of AF. ERAA were another predictor for procedural failure (HR 15.2; 95 % CI (6.42-35.99; p = 0.019).Conclusions: ERAA occurred in the third of the patients after PV second-generation CBA and are strongly associated with procedural failure. Longer duration of AF history and persistent AF are independent predictors of AF's early and late recurrence. [ABSTRACT FROM AUTHOR]

Background: Noninvasive myocardial imaging modalities, such as cardiac magnetic resonance (CMR), single photon emission computed tomography (SPECT), and Positron emission tomography (PET), are well-established and extensively used to detect cardiac amyloid (CA). The purpose of this study is to directly compare CMR, SPECT, and PET scans in the diagnosis of CA, and to provide evidence for further scientific research and clinical decision-making.Methods: PubMed, Embase, and Cochrane Library were searched. Studies used CMR, SPECT and/or PET for the diagnosis of CA were included. Pooled sensitivity, specificity, positive and negative likelihood ratio (LR), diagnostic odds ratio (DOR), their respective 95% confidence intervals (CIs) and the area under the summary receiver operating characteristic (SROC) curve (AUC) were calculated. Quality assessment of included studies was conducted.Results: A total of 31 articles were identified for inclusion in this meta-analysis. The pooled sensitivities of CMR, SPECT and PET were 0.84, 0.98 and 0.78, respectively. Their respective overall specificities were 0.87, 0.92 and 0.95. Subgroup analysis demonstrated that 99mTc-HMDP manifested the highest sensitivity (0.99). 99mTc-PYP had the highest specificity (0.95). The AUC values of 99mTc-DPD, 99mTc-PYP, 99mTc-HMDP were 0.89, 0.99, and 0.99, respectively. PET scan with 11C-PIB demonstrated a pooled sensitivity of 0.91 and specificity of 0.97 with an AUC value of 0.98.Conclusion: Our meta-analysis reveals that SEPCT scans present better diagnostic performance for the identification of CA as compared with other two modalities. [ABSTRACT FROM AUTHOR]

Background: Among people living with HIV (PLHIV), more flexible and sensitive tuberculosis (TB) screening tools capable of detecting both symptomatic and subclinical active TB are needed to (1) reduce morbidity and mortality from undiagnosed TB; (2) facilitate scale-up of tuberculosis preventive therapy (TPT) while reducing inappropriate prescription of TPT to PLHIV with subclinical active TB; and (3) allow for differentiated HIV-TB care.Methods and Findings: We used Botswana XPRES trial data for adult HIV clinic enrollees collected during 2012 to 2015 to develop a parsimonious multivariable prognostic model for active prevalent TB using both logistic regression and random forest machine learning approaches. A clinical score was derived by rescaling final model coefficients. The clinical score was developed using southern Botswana XPRES data and its accuracy validated internally, using northern Botswana data, and externally using 3 diverse cohorts of antiretroviral therapy (ART)-naive and ART-experienced PLHIV enrolled in XPHACTOR, TB Fast Track (TBFT), and Gugulethu studies from South Africa (SA). Predictive accuracy of the clinical score was compared with the World Health Organization (WHO) 4-symptom TB screen. Among 5,418 XPRES enrollees, 2,771 were included in the derivation dataset; 67% were female, median age was 34 years, median CD4 was 240 cells/μL, 189 (7%) had undiagnosed prevalent TB, and characteristics were similar between internal derivation and validation datasets. Among XPHACTOR, TBFT, and Gugulethu cohorts, median CD4 was 400, 73, and 167 cells/μL, and prevalence of TB was 5%, 10%, and 18%, respectively. Factors predictive of TB in the derivation dataset and selected for the clinical score included male sex (1 point), ≥1 WHO TB symptom (7 points), smoking history (1 point), temperature >37.5°C (6 points), body mass index (BMI) <18.5kg/m2 (2 points), and severe anemia (hemoglobin <8g/dL) (3 points). Sensitivity using WHO 4-symptom TB screen was 73%, 80%, 94%, and 94% in XPRES, XPHACTOR, TBFT, and Gugulethu cohorts, respectively, but increased to 88%, 87%, 97%, and 97%, when a clinical score of ≥2 was used. Negative predictive value (NPV) also increased 1%, 0.3%, 1.6%, and 1.7% in XPRES, XPHACTOR, TBFT, and Gugulethu cohorts, respectively, when the clinical score of ≥2 replaced WHO 4-symptom TB screen. Categorizing risk scores into low (<2), moderate (2 to 10), and high-risk categories (>10) yielded TB prevalence of 1%, 1%, 2%, and 6% in the lowest risk group and 33%, 22%, 26%, and 32% in the highest risk group for XPRES, XPHACTOR, TBFT, and Gugulethu cohorts, respectively. At clinical score ≥2, the number needed to screen (NNS) ranged from 5.0 in Gugulethu to 11.0 in XPHACTOR. Limitations include that the risk score has not been validated in resource-rich settings and needs further evaluation and validation in contemporary cohorts in Africa and other resource-constrained settings.Conclusions: The simple and feasible clinical score allowed for prioritization of sensitivity and NPV, which could facilitate reductions in mortality from undiagnosed TB and safer administration of TPT during proposed global scale-up efforts. Differentiation of risk by clinical score cutoff allows flexibility in designing differentiated HIV-TB care to maximize impact of available resources. [ABSTRACT FROM AUTHOR]

Part 2 of this paper presents an analysis of variance (ANOVA) for investigating the precedence of the various parameters, and the effects of varying these parameters, in assessment of burn injury resulting from the exposure of skin surface to heat sources. A one-dimensional model based on the finite difference method (FDM), as implemented in a spreadsheet software application, is applied to the assessment of burn injury. Henriques' theory of skin burns is used for determining the spatial and temporal extent of tissue damage. The ranks of the effects of various factors were obtained. It was found that the highest ranked factor is the initial tissue temperature followed by the thermal conductivity of the epidermal layer. The effect of blood perfusion rate is ranked much below the combinations of other factors. The results from the present numerical experiment agree well with the results obtained by Palla. Sensitivity analysis of the critical exposure levels was also carried out and results are discussed. In this study, the effects of the various parameters on injury threshold were investigated. Again, the results indicate that the four parameters: thermal conductivity of the epidermis and dermis, convective heat transfer coefficient and initial tissue temperature, have a pronounced influence on assessing the burn injury threshold. It was also found that fat thermal conductivity and blood perfusion rate have no obvious effect on injury threshold. A two-dimensional analysis was further conducted to determine the sensitivity of the predicted injury to the values of frequency factor, P, and apparent activation energy, deltaE, used in the models. Part 1 of this study details the development of the computer models based on the one- and two-dimensional bioheat equations. [ABSTRACT FROM AUTHOR]

Background: Noncontrast cardiac T1 times are increased in dialysis patients which might indicate fibrotic alterations in uremic cardiomyopathy.Purpose: To explore the application of the texture analysis (TA) of T1 images in the assessment of myocardial alterations in dialysis patients.Study Type: Case-control study.Population: A total of 117 subjects, including 22 on hemodialysis, 44 on peritoneal dialysis, and 51 healthy controls.Field Strength: A 3 T, steady-state free precession (SSFP) sequence, modified Look-Locker imaging (MOLLI).Assessment: Two independent, blinded researchers manually delineated endocardial and epicardial borders of the left ventricle (LV) on midventricular T1 maps for TA.Statistical Tests: Texture feature selection was performed, incorporating reproducibility verification, machine learning, and collinearity analysis. Multivariate linear regressions were performed to examine the independent associations between the selected texture features and left ventricular function in dialysis patients. Texture features' performance in discrimination was evaluated by sensitivity and specificity. Reproducibility was estimated by the intraclass correlation coefficient (ICC).Results: Dialysis patients had greater T1 values than normal (P < 0.05). Five texture features were filtered out through feature selection, and four showed a statistically significant difference between dialysis patients and healthy controls. Among the four features, vertical run-length nonuniformity (VRLN) had the most remarkable difference among the control and dialysis groups (144 ± 40 vs. 257 ± 74, P < 0.05), which overlap was much smaller than Global T1 times (1268 ± 38 vs. 1308 ± 46 msec, P < 0.05). The VRLN values were notably elevated (cutoff = 170) in dialysis patients, with a specificity of 97% and a sensitivity of 88%, compared with T1 times (specificity = 76%, sensitivity = 60%). In dialysis patients, VRLN was significantly and independently associated with left ventricular ejection fraction (P < 0.05), global longitudinal strain (P < 0.05), radial strain (P < 0.05), and circumferential strain (P < 0.05); however, T1 was not.Data Conclusion: The texture features obtained by TA of T1 images and VRLN may be a better parameter for assessing myocardial alterations than T1 times.Level Of Evidence: 4 TECHNICAL EFFICACY: Stage 3. [ABSTRACT FROM AUTHOR]

Background: No clinical studies to date have compared the inspiratory and expiratory airway lumen area between supine and standing positions. Thus, the aims of this study were twofold: (1) to compare inspiratory and expiratory airway lumen area (IAA and EAA, respectively) on computed tomography (CT) among supine and standing positions; and (2) to investigate if IAA and EAA are associated with lung function abnormality in patients with chronic obstructive pulmonary disease (COPD).Methods: Forty-eight patients with COPD underwent both low-dose conventional (supine position) and upright CT (standing position) during inspiration and expiration breath-holds and a pulmonary function test (PFT) on the same day. We measured the IAA and EAA in each position.Results: For the trachea to the third-generation bronchi, the IAA was significantly larger in the standing position than in the supine position (4.1-4.9% increase, all p < 0.05). The EAA of all bronchi was significantly larger in the standing position than in the supine position (9.7-62.5% increases, all p < 0.001). The correlation coefficients of IAA in the standing position and forced expiratory volume in 1 s were slightly higher than those in the supine position. The correlation coefficients of EAA or EAA/IAA in the standing position and residual volume, and the inspiratory capacity/total lung capacity ratio were higher than those in the supine position.Conclusions: Airway lumen areas were larger in the standing position than in the supine position. IAAs reflect airway obstruction, and EAAs reflect lung hyperinflation. Upright CT might reveal these abnormalities more precisely. Trial registration University Hospital Medical Information Network (UMIN 000026587), Registered 17 March 2017. URL: https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000030456 . [ABSTRACT FROM AUTHOR]

The structural response of a large artery is characteristically complex and includes the highly non-linear, history-dependent response of a nonhomogeneous anisotropic structure undergoing finite deformations. The mechanics of the arterial wall has been studied for nearly two centuries. The goals of such research range from the desire to have a basic knowledge and understanding of the mechanics and physiology of this complex structure to the need for data and methods for the design of arterial prostheses. In this paper, the models for arterial wall behaviour are critically reviewed. Firstly, the structure and general characteristics of the arterial wall are discussed. This is followed by a comprehensive review of the constitutive laws. Finally, structural analyses of the arterial wall by mathematical and numerical methods are discussed. Predictions using the authors' preferred models give focus to important issues, and in Part 2 the review and predictions are extended to the fluid solid coupled situation. [ABSTRACT FROM AUTHOR]

Aims: To evaluate diagnostic performance of glomerular filtration rate (GFR) estimated by modification of diet in renal disease (MDRD), chronic kidney disease epidemiology collaboration (CKD-EPI), full age spectrum (FAS), and revised Lund-Malmö (r-LM) equations in adults with diabetes.Methods: Individuals were included in this cross-sectional study if they had at least 1 measurement of technetium-99m diethylenetriamine-pentaacetic acid (99mTc-DTPA) GFR (mGFR) and serum creatinine (1487 patients with 2703 measures). GFR calculated by estimation equations was compared with mGFR. Diagnostic performance was assessed using concordance correlation coefficient (CCC), bias, precision, accuracy, reduced major axis regression (RMAR), and Bland-Altman plot. Analysis was repeated in subgroups based on sex, diabetes type, Hemoglobin A1C, and GFR level.Results: Of all patients, 1189 (86%) had type 2 diabetes. Mean mGFR, MDRD, CKD-EPI, FAS, and revised Lund-Malmö eGFR were 66, 72, 74, 71, and 67 mL/min/1.73m2, respectively. Overall, the r-LM had the highest CCC (0.83), lowest bias (-1.4 mL/min/1.73 m2), highest precision (16.2 mL/min/1.73 m2), and highest accuracy (P10 = 39%). The RMAR (slope, intercept) in r-LM, FAS, MDRD, and CKD-EPI was 1.18, -13.35; 0.97, -2.9; 1, -6.4, and 1.04, -11.3, respectively. The Bland-Altman plot showed that r-LM had the lowest mean difference and the narrowest 95% limit of agreement (-1.0, 54.1 mL/min/1.73 m2), while mean difference was more than 5-fold higher in FAS, MDRD, and CKD-EPI (-5.2, -6.3, and -8.2, respectively).Conclusions: In adults with diabetes the revised Lund-Malmö performs better than MDRD, CKD-EPI, and FAS in calculating point estimates of GFR. [ABSTRACT FROM AUTHOR]

Background: Barrett's esophagus is the precursor to the highly lethal esophageal adenocarcinoma. Risk prediction models have been developed to assist in its detection, potentially improving early identification and treatment of esophageal adenocarcinoma. Six models have been developed.Aims: To externally validate three models (Rubenstein, Thrift, and Baldwin-Hunter models) and compare them to a fourth risk prediction model (Ireland model) for Barrett's esophagus.Methods: Data from 120 Barrett's cases and 235 population controls were available to externally validate the three models. Discriminatory ability of these models was assessed by the area under the receiver operating characteristic curve. Calibration was assessed with the calibration slope, Hosmer-Lemeshow test, and Lowess smoother calibration plot. Following external validation, diagnostic accuracy of the three models was compared to that of the Ireland model.Results: On external validation, the Rubenstein model had an area under the receiver operating characteristic curve of 0.71 and was well calibrated (Hosmer-Lemeshow test, p = 0.67). Likewise, the Thrift and Baldwin-Hunter models had similar discrimination (0.71 and 0.70, respectively) and were also well calibrated (p = 0.69 and p = 0.28). Our previous external validation of the Ireland model provided an area under the receiver operating characteristic curve of 0.83 and was well calibrated (p = 0.14). The Ireland model demonstrated a statistically significantly greater area under the receiver operating characteristic curve than the Rubenstein (p = 0.02), Thrift (p = 0.001), and Baldwin-Hunter (p = 0.002) models.Conclusion: We externally validated the Rubenstein, Thrift, and Baldwin-Hunter risk prediction models and compared them to the Ireland model. The Ireland model demonstrated improved accuracy, albeit with slightly poorer calibration. [ABSTRACT FROM AUTHOR]

Objective: To compare the value of using one-stop magnetic resonance imaging (MRI) vs standard radiological imaging as a supplement to transvaginal ultrasonography (TVS) for the preoperative assessment of patients with endometriosis referred for surgery in a tertiary care academic center.Methods: This prospective observational study compared the diagnostic value of the standard preoperative imaging practice of our center, which involves expert TVS complemented by intravenous urography (IVU) for the evaluation of the ureters and double-contrast barium enema (DCBE) for the evaluation of the rectum, sigmoid and cecum, with that of expert TVS complemented by a 'one-stop' MRI examination evaluating the upper abdomen, pelvis, kidneys and ureters as well as rectum and sigmoid on the same day, for the preoperative triaging of 74 women with clinically suspected deep endometriosis. The findings at laparoscopy were considered the reference standard. Patients were stratified according to their need for monodisciplinary surgical approach, carried out by gynecologists only, or multidisciplinary surgical approach, involving abdominal surgeons and/or urologists, based on the extent to which endometriosis affected the reproductive organs, bowel, ureters, bladder or other abdominal organs.Results: Our standard preoperative imaging approach and the combined findings of TVS and MRI had similar diagnostic performance, resulting in correct stratification for a monodisciplinary or a multidisciplinary surgical approach of 67/74 (90.5%) patients. However, there were differences between the estimation of the severity of disease by DCBE and MRI. The severity of rectal involvement was underestimated in 2.7% of the patients by both TVS and DCBE, whereas it was overestimated in 6.8% of the patients by TVS and/or DCBE.Conclusions: Complementary to expert TVS, 'one-stop' MRI can predict intraoperative findings equally well as standard radiological imaging (IVU and DCBE) in patients referred for endometriosis surgery in a tertiary care academic center. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

Objective: Commercially available business (CAB) datasets for food environments have been investigated for error in large urban contexts and some rural areas, but there is a relative dearth of literature that reports error across regions of variable rurality. The objective of the current study was to assess the validity of a CAB dataset using a government dataset at the provincial scale.Design: A ground-truthed dataset provided by the government of Newfoundland and Labrador (NL) was used to assess a popular commercial dataset. Concordance, sensitivity, positive-predictive value (PPV) and geocoding errors were calculated. Measures were stratified by store types and rurality to investigate any association between these variables and database accuracy.Setting: NL, Canada.Participants: The current analysis used store-level (ecological) data.Results: Of 1125 stores, there were 380 stores that existed in both datasets and were considered true-positive stores. The mean positional error between a ground-truthed and test point was 17·72 km. When compared with the provincial dataset of businesses, grocery stores had the greatest agreement, sensitivity = 0·64, PPV = 0·60 and concordance = 0·45. Gas stations had the least agreement, sensitivity = 0·26, PPV = 0·32 and concordance = 0·17. Only 4 % of commercial data points in rural areas matched every criterion examined.Conclusions: The commercial dataset exhibits a low level of agreement with the ground-truthed provincial data. Particularly retailers in rural areas or belonging to the gas station category suffered from misclassification and/or geocoding errors. Taken together, the commercial dataset is differentially representative of the ground-truthed reality based on store-type and rurality/urbanity. [ABSTRACT FROM AUTHOR]

Background: The onset of venous thromboembolism is insidious and the prognosis is poor. In this study, we aimed to construct a VTE risk warning model and testified its clinical application value.Methods: Preliminary construction of the VTE risk warning model was carried out according to the independent risk warning indicators of VTE screened by Logistic regression analysis. The truncated value of screening VTE was obtained and the model was evaluated. ROC curve analysis was used to compare the test of Caprini risk assessment scale and VTE risk warning model. The cut-off value of the VTE risk warning model was used to evaluate the test effectiveness of the model for VTE patients with validation data set.Results: The VTE risk warning model is p = ex / (1+ ex), x = - 4.840 + 2.557 • X10(1) + 1.432 • X14(1) + 2.977 • X15(1) + 3.445 • X18(1) + 1.086 • X25(1) + 0.249 • X34 + 0.282 • X41. ROC curve results show that: AUC (95%CI), cutoff value, sensitivity, specificity, accuracy, Youden index, Caprini risk assessment scale is 0.596 (0.552, 0.638), 5, 26.07, 96.50, 61.3%, 0.226, VTE risk warning model is 0.960 (0.940, 0.976), 0.438, 92.61, 91.83, 92.2%, 0.844, respectively, with statistically significant differences (Z = 14.521, P < 0.0001). The accuracy and Youden index of VTE screening using VTE risk warning model were 81.8 and 62.5%, respectively.Conclusions: VTE risk warning model had high accuracy in predicting VTE occurrence in hospitalized patients. Its test performance was better than Caprini risk assessment scale. It also had high test performance in external population. [ABSTRACT FROM AUTHOR]

Objective: The present study was undertaken to assess the comparative responsiveness of outcome measures used for the assessment of pain and function in individuals with osteoarthritis (OA) of the first metatarsophalangeal (MTP) joint.Methods: Eighty-eight patients (mean ± SD age 57.2 ± 10.2 years) with OA of the first MTP joint who participated in a randomized trial completed the Foot Health Status Questionnaire (FHSQ), the Foot Function Index Revised Short Form (FFI-RS), and 100-mm visual analog scales (VAS) of pain and stiffness at baseline and 12 weeks. Responsiveness of the subscales for each outcome measure was determined using paired t-tests, Cohen's d coefficient, the standardized response mean (SRM), and the Guyatt index (GI). Sample size estimations were calculated based on minimal important differences (MIDs).Results: All outcome measures were sensitive to change and demonstrated at least medium effect sizes. Three outcome measures exhibited large or very large effect sizes for Cohen's d coefficient, the SRM, and the GI: the FHSQ pain subscale (d = 1.03; SRM 1.10, GI score 1.30), the FFI-RS pain subscale (d = 1.09; SRM 1.05, GI score 1.73), and the 100-mm VAS of pain severity while walking (d = 1.22; SRM 1.07, GI score 1.78). Sample size calculations indicated that between 20 and 33 participants per group would be required to detect MIDs using these measures.Conclusion: The FHSQ pain subscale, FFI-RS pain subscale, and the 100-mm VAS of pain severity while walking are the most responsive outcome measures for the assessment of pain and function in individuals with OA of the first MTP joint. These findings provide useful information to guide researchers in selecting appropriate outcome measures for use in future clinical trials. [ABSTRACT FROM AUTHOR]

Rationale: Although proposed as a clinical prompt to sepsis based on predictive validity for mortality, the Quick Sepsis-related Organ Failure Assessment (qSOFA) score is often used as a screening tool, which requires high sensitivity.Objectives: To assess the predictive accuracy of qSOFA for mortality in Brazil, focusing on sensitivity.Methods: We prospectively collected data from two cohorts of emergency department and ward patients. Cohort 1 included patients with suspected infection but without organ dysfunction or sepsis (22 hospitals: 3 public and 19 private). Cohort 2 included patients with sepsis (54 hospitals: 24 public and 28 private). The primary outcome was in-hospital mortality. The predictive accuracy of qSOFA was examined considering only the worst values before the suspicion of infection or sepsis.Measurements and Main Results: Cohort 1 contained 5,460 patients (mortality rate, 14.0%; 95% confidence interval [CI], 13.1-15.0), among whom 78.3% had a qSOFA score less than or equal to 1 (mortality rate, 8.3%; 95% CI, 7.5-9.1). The sensitivity of a qSOFA score greater than or equal to 2 for predicting mortality was 53.9% and the 95% CI was 50.3 to 57.5. The sensitivity was higher for a qSOFA greater than or equal to 1 (84.9%; 95% CI, 82.1-87.3), a qSOFA score greater than or equal to 1 or lactate greater than 2 mmol/L (91.3%; 95% CI, 89.0-93.2), and systemic inflammatory response syndrome plus organ dysfunction (68.7%; 95% CI, 65.2-71.9). Cohort 2 contained 4,711 patients, among whom 62.3% had a qSOFA score less than or equal to 1 (mortality rate, 17.3%; 95% CI, 15.9-18.7), whereas in public hospitals the mortality rate was 39.3% (95% CI, 35.5-43.3).Conclusions: A qSOFA score greater than or equal to 2 has low sensitivity for predicting death in patients with suspected infection in a developing country. Using a qSOFA score greater than or equal to 2 as a screening tool for sepsis may miss patients who ultimately die. Using a qSOFA score greater than or equal to 1 or adding lactate to a qSOFA score greater than or equal to 1 may improve sensitivity.Clinical trial registered with www.clinicaltrials.gov (NCT03158493). [ABSTRACT FROM AUTHOR]

Background and Aims: The high prevalence of nonalcoholic fatty liver disease (NAFLD) in the general population warrants determining whether pocket-sized ultrasound devices (PoCUS) might serve as point-of-care screening for NAFLD in busy office practices.Methods: One hundred adult subjects undergoing conventional abdominal ultrasound (US) examinations for various indications were screened by PoCUS immediately prior to the conventional US procedure. The PoCUS examination only assessed the presence or absence of excess fat. Assessment of other liver pathology was not performed. Investigators (conventional US: an experienced radiologist and PoCUS: a general internist recently trained in the use of PoCUS) were blinded to the results of the alternative imaging.Results: Forty patients (40%) had fatty infiltration of the liver on both conventional US and PoCUS, and 49 (49%) were negative by both modalities. A consensus was reached in two of the 11 remaining subjects with initially discrepant results. The overall sensitivity and specificity of PoCUS relative to conventional US were 91% and 88%, respectively.Conclusions: These findings support the use of PoCUS by a trained physician for point-of-care screening of patients at risk for NAFLD. [ABSTRACT FROM AUTHOR]

Background: Metabolic syndrome (MetSyn) predicted future development of World Trade Center lung injury (WTC-LI) in a subgroup of firefighters who never smoked and were male. An intracohort validation of MetSyn as a predictor of WTC-LI is examined in the cohort exposed to the World Trade Center (WTC) that has been followed longitudinally for 16 years.Methods: Results of pulmonary function tests (n = 98,221) in workers exposed to the WTC (n = 9,566) were evaluated. A baseline cohort of firefighters who had normal FEV1 before 9/11 and who had had serum drawn before site closure on July 24, 2002 (n = 7,487) was investigated. Case subjects with WTC-LI (n = 1,208) were identified if they had at least two measured instances of FEV1 less than the lower limit of normal (LLN). Cox proportional hazards modeled early MetSyn biomarker ability to predict development of FEV1 less than the LLN.Results: Case subjects were more likely to smoke, be highly exposed, and have MetSyn. There was a significant exposure dose response; the individuals most highly exposed had a 30.1% increased risk of developing WTC-LI, having MetSyn increased risk of developing WTC-LI by 55.7%, and smoking increased risk by 15.2%. There was significant interaction between smoking and exposure.Conclusions: We validated the usefulness of MetSyn to predict future WTC-LI in a larger population of individuals who were exposed. MetSyn defined by dyslipidemia, insulin resistance, and cardiovascular disease suggests that systemic inflammation can contribute to future lung function loss. [ABSTRACT FROM AUTHOR]

Objective: The aim of our study was to assess charts proposed for international use in the Intergrowth-21st Project.Methods: Ultrasound data were collected from 43,923 healthy singleton pregnancies examined at 18-23 weeks of gestation in the Netherlands. Fetal measurements were converted into Z-scores using previous and current Dutch reference charts and Intergrowth charts. The distributions of the Z-scores were compared with the expected standard normal distribution.Results: In the Dutch population, Intergrowth curves perform well for head circumference and biparietal diameter, but not for abdominal circumference (AC, Z- score = 0.43) and femur length (FL, Z-score = 0.26). Similar findings have been reported in other European countries. Compared with the population in the Intergrowth study, Dutch women are relatively tall (170 vs. 162 cm) and sturdy (67 vs. 61 kg) with a moderately high BMI. Maternal size, in particular maternal height, is positively correlated with birthweight.Conclusions: Whilst the establishment of the Intergrowth charts is an important step towards worldwide uniformity, for now locally derived charts still perform better, especially for AC and FL. Results from our validation study indicate that distinction between normal and pathologically small babies may be improved by taking maternal size into account. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to determine if auscultation or a point-of-care scan could reduce the need for standard echocardiography (transthoracic echocardiogram (TTE)) in community patients with asymptomatic murmurs.Methods: Requests from general practitioners were directed to a new murmur clinic. Auscultation and a point-of-care scan were performed by a cardiologist between 1 October 2013 and 31 December 2014 and by a scientist between 21 July 2015 and 9 May 2017.Results: In the first phase (cardiologist), there were 75 patients, mean age 54 (56 women), and in the second phase there were 100 patients, mean age 60 (76 women). In the total population of 175, abnormalities were shown on TTE in 52 (30%), on point-of-care scan in 52 (30%) and predicted on auscultation in 45 (26%) (p=0.125; 95% CI -0.02 to 0.29). The sensitivity of auscultation was not significantly different for the cardiologist (91%) as for the scientist (83%) (p=0.18; 95% CI -0.22 to 0.175) and the specificity was 100% for both. Accuracy was 97% for the cardiologist and 95% for the scientist. For the point-of-care scan, the sensitivity, specificity, positive and negative predictive values and accuracy were 100% for both cardiologist and scientist.Conclusion: Most patients in a specialist murmur clinic had normal auscultation and point-of-care scans and no additional valve disease was detected by standard echocardiography. This suggests that a murmur clinic is a valid model for reducing demand on hospital echocardiography services. [ABSTRACT FROM AUTHOR]

Background: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease. Severe NAFLD with advanced fibrosis results in substantial morbidity and mortality. Associated with metabolic syndrome, NAFLD is often initially clinically silent, yet intensive lifestyle intervention with 7% or greater weight loss can improve or resolve NAFLD. Using a Veterans Health Administration (VHA) liver biopsy cohort, we evaluated simple noninvasive fibrosis scoring systems to identify NAFLD with advanced fibrosis (or severe disease) to assist providers.Methods: In our retrospective study of a national VHA sample of patients with biopsy-proven NAFLD or normal liver (2005-2015), we segregated patients by fibrosis stage (0-4). Non-NAFLD liver disease was excluded. We evaluated the diagnostic accuracy of the NAFLD fibrosis score (NFS), fibrosis-4 calculator (FIB-4), aspartate aminotransferase-to-alanine aminotransferase ratio (AST/ALT ratio), AST-to-platelet ratio index (APRI), and body mass index, AST/ALT ratio, and diabetes (BARD) score by age groups.Results: We included 329 patients with well-defined liver histology (296 NAFLD and 33 normal controls without fibrosis), in which 92 (28%) had advanced (stage 3-4) fibrosis. Across all age groups, NFS and FIB-4 best predicted advanced fibrosis (NFS with 0.676 threshold: AUROC 0.71-0.76, LR + 2.30-22.05, OR 6.00-39.58; FIB-4 with 2.67 threshold: AUROC of 0.62-0.80, LR + 4.70-27.45, OR 16.34-59.65).Conclusions: While NFS and FIB-4 scores exhibit good diagnostic accuracy, FIB-4 is optimal in identifying NAFLD advanced fibrosis in the VHA. Easily implemented as a point-of-care clinical test, FIB-4 can be useful in directing patients that are most likely to have advanced fibrosis to GI/hepatology consultation and follow-up. [ABSTRACT FROM AUTHOR]

Accurate seizure prediction will transform epilepsy management by offering warnings to patients or triggering interventions. However, state-of-the-art algorithm design relies on accessing adequate long-term data. Crowd-sourcing ecosystems leverage quality data to enable cost-effective, rapid development of predictive algorithms. A crowd-sourcing ecosystem for seizure prediction is presented involving an international competition, a follow-up held-out data evaluation, and an online platform, Epilepsyecosystem.org, for yielding further improvements in prediction performance. Crowd-sourced algorithms were obtained via the 'Melbourne-University AES-MathWorks-NIH Seizure Prediction Challenge' conducted at kaggle.com. Long-term continuous intracranial electroencephalography (iEEG) data (442 days of recordings and 211 lead seizures per patient) from prediction-resistant patients who had the lowest seizure prediction performances from the NeuroVista Seizure Advisory System clinical trial were analysed. Contestants (646 individuals in 478 teams) from around the world developed algorithms to distinguish between 10-min inter-seizure versus pre-seizure data clips. Over 10 000 algorithms were submitted. The top algorithms as determined by using the contest data were evaluated on a much larger held-out dataset. The data and top algorithms are available online for further investigation and development. The top performing contest entry scored 0.81 area under the classification curve. The performance reduced by only 6.7% on held-out data. Many other teams also showed high prediction reproducibility. Pseudo-prospective evaluation demonstrated that many algorithms, when used alone or weighted by circadian information, performed better than the benchmarks, including an average increase in sensitivity of 1.9 times the original clinical trial sensitivity for matched time in warning. These results indicate that clinically-relevant seizure prediction is possible in a wider range of patients than previously thought possible. Moreover, different algorithms performed best for different patients, supporting the use of patient-specific algorithms and long-term monitoring. The crowd-sourcing ecosystem for seizure prediction will enable further worldwide community study of the data to yield greater improvements in prediction performance by way of competition, collaboration and synergism.10.1093/brain/awy210_video1awy210media15817489051001. [ABSTRACT FROM AUTHOR]

Objective: Existing clinical prediction models (CPM) for short-term mortality after transcatheter aortic valve implantation (TAVI) have limited applicability in the UK due to moderate predictive performance and inconsistent recording practices across registries. The aim of this study was to derive a UK-TAVI CPM to predict 30-day mortality risk for benchmarking purposes.Methods: A two-step modelling strategy was undertaken: first, data from the UK-TAVI Registry between 2009 and 2014 were used to develop a multivariable logistic regression CPM using backwards stepwise regression. Second, model-updating techniques were applied using the 2013-2014 data, thereby leveraging new approaches to include frailty and to ensure the model was reflective of contemporary practice. Internal validation was performed by bootstrapping to estimate in-sample optimism-corrected performance.Results: Between 2009 and 2014, up to 6339 patients were included across 34 centres in the UK-TAVI Registry (mean age, 81.3; 2927 female (46.2%)). The observed 30-day mortality rate was 5.14%. The final UK-TAVI CPM included 15 risk factors, which included two variables associated with frailty. After correction for in-sample optimism, the model was well calibrated, with a calibration intercept of 0.02 (95% CI -0.17 to 0.20) and calibration slope of 0.79 (95% CI 0.55 to 1.03). The area under the receiver operating characteristic curve, after adjustment for in-sample optimism, was 0.66.Conclusion: The UK-TAVI CPM demonstrated strong calibration and moderate discrimination in UK-TAVI patients. This model shows potential for benchmarking, but even the inclusion of frailty did not overcome the need for more wide-ranging data and other outcomes might usefully be explored. [ABSTRACT FROM AUTHOR]

Background: To investigate the diagnostic value of dual-source computed tomography (DSCT) in the evaluation of tetralogy of Fallot (TOF)-associated extracardiac vascular abnormalities in pediatric patients compared with transthoracic echocardiography (TTE).Methods: One hundred and twenty-three pediatric patients diagnosed with TOF were included in this retrospective study. All patients underwent DSCT and TTE preoperatively. All associated extracardiac vascular abnormalities and their percentages were recorded. The diagnostic performances of DSCT and TTE were compared based on the surgical results. The image quality of DSCT was rated, and the effective radiation dose (ED) was calculated.Results: A total of 159 associated extracardiac vascular deformities were confirmed by surgery. Patent ductus arteriosus (36, 22.64%), right-sided aortic arch (29, 18.24%), and pulmonary valve stenosis (23, 14.47%) were the most common associated extracardiac vascular abnormalities. DSCT was superior to TTE in demonstrating associated extracardiac anomalies (diagnostic accuracy: 99.13% vs. 97.39%; sensitivity: 92.45% vs. 77.07%; specificity: 99.81% vs. 99.42%). The agreement on grading the image quality of DSCT was excellent (κ = 0.80), and the mean score of the image quality was 3.39 ± 0.50. The mean ED of DSCT was 0.86 ± 0.47 mSv.Conclusions: Compared to TTE, low-dose DSCT has high diagnostic accuracy in the depiction of associated extracardiac vascular anomalies in pediatric patients with TOF, and could provide more morphological details for surgeons. [ABSTRACT FROM AUTHOR]

Background: Risk of hepatocellular carcinoma (HCC) may be difficult to determine in the clinical setting.Aim: Develop a scoring system to forecast HCC risk among patients with chronic hepatitis C.Methods: Using data from the Chronic Hepatitis Cohort Study collected during 2005-2014, we derived HCC risk scores for males and females using an extended Cox model with aspartate aminotransferase-to-platelet ratio index (APRI) as a time-dependent variables and mean Kaplan-Meier survival functions from patient data at two study sites, and used data collected at two separate sites for external validation. For model calibration, we used the Greenwood-Nam-D'Agostino goodness-of-fit statistic to examine differences between predicted and observed risk.Results: Of 12,469 patients (1628 with a history of sustained viral response [SVR]), 504 developed HCC; median follow-up was 6 years. Final predictors in the model included age, alcohol abuse, interferon-based treatment response, and APRI. Point values, ranging from -3 to 14 (males) and -3 to 12 (females), were established using hazard ratios of the predictors aligned with 1-, 3-, and 5-year Kaplan-Meier survival probabilities of HCC. Discriminatory capacity was high (c-index 0.82 males and 0.84 females) and external calibration demonstrated no differences between predicted and observed HCC risk for 1-, 3-, and 5-year forecasts among males (all p values >0.97) and for 3- and 5-year risk among females (all p values >0.87).Conclusion: This scoring system, based on age, alcohol abuse history, treatment response, and APRI, can be used to forecast up to a 5-year risk of HCC among hepatitis C patients before and after SVR. [ABSTRACT FROM AUTHOR]

Objective: Observational study of patients with chest pain in primary care: determination of incidence, referral rate, diagnostic tests and (agreement between) working and final diagnoses.Methods: 118 general practitioners (GPs) in the Netherlands and Belgium recorded all patient contacts during  2weeks. Furthermore, patients presenting with chest pain were registered extensively. A follow-up form was filled in after 30 days.Results: 22 294 patient contacts were registered. In 281 (1.26%), chest pain was a reason for consulting the GP (mean age for men 54.4/women 53 years). In this cohort of 281 patients, in 38.1% of patients, acute coronary syndrome (ACS) was suspected at least temporarily during consultation, 40.2% of patients were referred to secondary care and 512 diagnostic tests were performed by GPs and consulted specialists. Musculoskeletal pain was the most frequent working (26.1%) and final diagnoses (33.1%). Potentially life-threatening diseases as final diagnosis (such as myocardial infarction) accounted for 8.4% of all chest pain cases. In 23.1% of cases, a major difference between working and final diagnoses was found, in 0.7% a severe disease was initially missed by the GP.Conclusion: Chest pain was present in 281 patients (1.26% of all consultations). Final diagnoses were mostly non-life-threatening. Nevertheless, in 8.4% of patients with chest pain, life-threatening underlying causes were identified. This seems reflected in the magnitude and wide variety of diagnostic tests performed in these patients by GPs and specialists, in the (safe) overestimation of life-threatening diseases by GPs at initial assessment and in the high referral rate we found. [ABSTRACT FROM AUTHOR]

Objective: The present study assessed systematic bias and the effects of data set error on the validity of food environment measures in two municipal and two commercial secondary data sets.Design: Sensitivity, positive predictive value (PPV) and concordance were calculated by comparing two municipal and two commercial secondary data sets with ground-truthed data collected within 800 m buffers surrounding twenty-six schools. Logistic regression examined associations of sensitivity and PPV with commercial density and neighbourhood socio-economic deprivation. Kendall's τ estimated correlations between density and proximity of food outlets near schools constructed with secondary data sets v. ground-truthed data.Setting: Vancouver, Canada.Subjects: Food retailers located within 800 m of twenty-six schools RESULTS: All data sets scored relatively poorly across validity measures, although, overall, municipal data sets had higher levels of validity than did commercial data sets. Food outlets were more likely to be missing from municipal health inspections lists and commercial data sets in neighbourhoods with higher commercial density. Still, both proximity and density measures constructed from all secondary data sets were highly correlated (Kendall's τ>0·70) with measures constructed from ground-truthed data.Conclusions: Despite relatively low levels of validity in all secondary data sets examined, food environment measures constructed from secondary data sets remained highly correlated with ground-truthed data. Findings suggest that secondary data sets can be used to measure the food environment, although estimates should be treated with caution in areas with high commercial density. [ABSTRACT FROM AUTHOR]

Objective: Patient-physician discordance in global assessment of disease activity concerns one-third of patients, but what does it reflect? We aimed to assess patient-physician discordance in psoriatic arthritis (PsA) and patient-reported domains of health (physical and psychological) associated with discordance.Methods: We analyzed the PsAID (Psoriatic Arthritis Impact of Disease), a cross-sectional, multicenter European study of patients with PsA according to expert opinion. Patient global assessment (PGA) and physician global assessment (PhGA) were rated on a 0-10 numeric rating scale. Discordance was defined as the difference (PGA-PhGA) and as the absolute difference |PGA-PhGA| ≥3 points. Determinants of PGA-PhGA were assessed by a stepwise multivariate linear regression among 12 physical and psychological aspects of impact: pain, skin problems, fatigue, ability to work/leisure, functional incapacity, feeling of discomfort, sleep disturbance, anxiety/fear, coping, embarrassment/shame, social participation, and depressive affects.Results: In 460 patients (mean ± SD age 50.6 ± 12.9 years, 52.2% female, mean ± SD disease duration 9.5 ± 9.5 years, mean ± SD Disease Activity Index for Psoriatic Arthritis score 30.8 ± 32.4, and 40.4% undergoing treatment with biologic agents), the mean ± SD PGA was higher than the mean PhGA, with a mean absolute difference of 1.9 ± 1.8 points. Discordance defined by |PGA-PhGA| ≥3 of 10 concerned 134 patients (29.1%), and 115 patients (85.8% of the patients with discordance) had PGA>PhGA. Higher fatigue (β = 0.14), lower self-perceived coping (β = 0.23), and impaired social participation (β = 0.16) were independently associated with a higher difference (PGA-PhGA).Conclusion: Discordance concerned 29.1% of these patient/physician dyads, mainly by PGA>PhGA. Factors associated with discordance were psychological rather than physical domains of health. Discordance was more frequent in patients in remission, indicating more work is needed on the patient perspective regarding disease activity. [ABSTRACT FROM AUTHOR]

Aims: Complex ablation procedures are supported by accurate representation of an increasing variety of electrophysiological and imaging data within electroanatomic mapping systems (EMS). This study aims to develop a novel method for representing multiple complementary datasets on a single cardiac chamber model. Validation of the system and its application to both atrial and ventricular arrhythmias is examined.Methods and Results: Dot mapping was conceived to display multiple datasets by utilizing quantitative surface shading to represent one dataset and finely spaced dots to represent others. Dot positions are randomized within triangular (surface meshes) or tetrahedral (volumetric meshes) simplices making the approach directly transferrable to contemporary EMS. Test data representing uniform electrical activation (n = 10) and focal scarring (n = 10) were used to test dot mapping data perception accuracy. User experience of dot mapping with atrial and ventricular clinical data is evaluated. Dot mapping ensured constant screen dot density for regions of uniform dataset values, regardless of user manipulation of the cardiac chamber. Perception accuracy of dot mapping was equivalent to colour mapping for both propagation direction (1.5 ± 1.8 vs. 4.8 ± 5.3°, P = 0.24) and focal source localization (1.1 ± 0.7 vs. 1.4 ± 0.5 mm, P = 0.88). User acceptance testing revealed equivalent diagnostic accuracy and display fidelity when compared with colour mapping.Conclusion: Dot mapping provides the unique ability to display multiple datasets from multiple sources on a single cardiac chamber model. The visual combination of multiple datasets may facilitate interpretation of complex electrophysiological and imaging data. [ABSTRACT FROM AUTHOR]