Study of the thermal effects induced by magnetic resonance on endocardial leads: numerical models and experimental validation

Magnetic resonance imaging (MRI) is today precluded to patients bearing active implantable medical devices AIMDs). The great advantages related to this diagnostic modality, together with the increasing number of people benefiting from implantable devices, in particular pacemakers(PM)and carioverter/defibrillators (ICD), is prompting the scientific community the study the possibility to extend MRI also to implanted patients. The MRI induced specific absorption rate (SAR) and the consequent heating of biological tissues is one of the major concerns that makes patients bearing metallic structures contraindicated for MRI scans. To date, both in-vivo and in-vitro studies have demonstrated the potentially dangerous temperature increase caused by the radiofrequency (RF) field generated during MRI procedures in the tissues surrounding thin metallic implants. On the other side, the technical evolution of MRI scanners and of AIMDs together with published data on the lack of adverse events have reopened the interest in this field and suggest that, under given conditions, MRI can be safely performed also in implanted patients. With a better understanding of the hazards of performing MRI scans on implanted patients as well as the development of MRI safe devices, we may soon enter an era where the ability of this imaging modality may be more widely used to assist in the appropriate diagnosis of patients with devices. In this study both experimental measures and numerical analysis were performed. Aim of the study is to systematically investigate the effects of the MRI RF filed on implantable devices and to identify the elements that play a major role in the induced heating. Furthermore, we aimed at developing a realistic numerical model able to simulate the interactions between an RF coil for MRI and biological tissues implanted with a PM, and to predict the induced SAR as a function of the particular path of the PM lead. The methods developed and validated during the PhD program led to the design of an experimental framework for the accurate measure of PM lead heating induced by MRI systems. In addition, numerical models based on Finite-Differences Time-Domain (FDTD) simulations were validated to obtain a general tool for investigating the large number of parameters and factors involved in this complex phenomenon. The results obtained demonstrated that the MRI induced heating on metallic implants is a real risk that represents a contraindication in extending MRI scans also to patient bearing a PM, an ICD, or other thin metallic objects. On the other side, both experimental data and numerical results show that, under particular conditions, MRI procedures might be consider reasonably safe also for an implanted patient. The complexity and the large number of variables involved, make difficult to define a unique set of such conditions: when the benefits of a MRI investigation cannot be obtained using other imaging techniques, the possibility to perform the scan should not be immediately excluded, but some considerations are always needed.

Validation of the Asthma Predictive Index and comparison with simpler clinical prediction rules

Background The loose and stringent Asthma Predictive Indices (API), developed in Tucson, are popular rules to predict asthma in preschool children. To be clinically useful, they require validation in different settings. Objective To assess the predictive performance of the API in an independent population and compare it with simpler rules based only on preschool wheeze. Methods We studied 1954 children of the population-based Leicester Respiratory Cohort, followed up from age 1 to 10 years. The API and frequency of wheeze were assessed at age 3 years, and we determined their association with asthma at ages 7 and 10 years by using logistic regression. We computed test characteristics and measures of predictive performance to validate the API and compare it with simpler rules. Results The ability of the API to predict asthma in Leicester was comparable to Tucson: for the loose API, odds ratios for asthma at age 7 years were 5.2 in Leicester (5.5 in Tucson), and positive predictive values were 26% (26%). For the stringent API, these values were 8.2 (9.8) and 40% (48%). For the simpler rule early wheeze, corresponding values were 5.4 and 21%; for early frequent wheeze, 6.7 and 36%. The discriminative ability of all prediction rules was moderate (c statistic ≤ 0.7) and overall predictive performance low (scaled Brier score < 20%). Conclusion Predictive performance of the API in Leicester, although comparable to the original study, was modest and similar to prediction based only on preschool wheeze. This highlights the need for better prediction rules.

Development and validation of a liquid chromatography-tandem mass spectrometry method for the quantitation of synthetic cannabinoids of the aminoalkylindole type and methanandamide in serum and its application to forensic samples

After the discovery of synthetic cannabimimetic substances in 'Spice'-like herbal mixtures marketed as 'incense' or 'plant fertilizer' the active compounds have been declared as controlled substances in several European countries. As expected, a monitoring of new herbal mixtures which continue to appear on the market revealed that shortly after control measures have been taken by legal authorities, other compounds were added to existing mixtures and to new products. Several compounds of the aminoalkylindole type have been detected so far in herbal mixtures but still their consumption cannot be detected by commonly used drug-screening procedures, encouraging drug users to substitute cannabis with those products. There is a increasing demand on the part of police authorities, hospitals and psychiatrists for detection and quantification of synthetic cannabinoids in biological samples originating from psychiatric inpatients, emergency units or assessment of fitness to drive. Therefore, a liquid chromatography-tandem mass spectrometry method after liquid-liquid extraction for the quantitation of JWH-015, JWH-018, JWH-073, JWH-081, JWH 200, JWH-250, WIN 55,212-2 and methanandamide and the detection of JWH-019 and JWH-020 in human serum has been developed and fully validated according to guidelines for forensic toxicological analyses. The method was successfully applied to 101 serum samples from 80 subjects provided by hospitals, detoxification and therapy centers, forensic psychiatric centers and police authorities. Fifty-seven samples or 56.4% were found positive for at least one aminoalkylindole. JWH-019, JWH-020, JWH-200, WIN 55,212-2 and methanandamide were not detected in any of the analyzed samples.

A realistic validation study of a new nitrogen multiple-breath washout system

Background For reliable assessment of ventilation inhomogeneity, multiple-breath washout (MBW) systems should be realistically validated. We describe a new lung model for in vitro validation under physiological conditions and the assessment of a new nitrogen (N2)MBW system. Methods The N2MBW setup indirectly measures the N2 fraction (FN2) from main-stream carbon dioxide (CO2) and side-stream oxygen (O2) signals: FN2 = 1−FO2−FCO2−FArgon. For in vitro N2MBW, a double chamber plastic lung model was filled with water, heated to 37°C, and ventilated at various lung volumes, respiratory rates, and FCO2. In vivo N2MBW was undertaken in triplets on two occasions in 30 healthy adults. Primary N2MBW outcome was functional residual capacity (FRC). We assessed in vitro error (√[difference]2) between measured and model FRC (100–4174 mL), and error between tests of in vivo FRC, lung clearance index (LCI), and normalized phase III slope indices (Sacin and Scond). Results The model generated 145 FRCs under BTPS conditions and various breathing patterns. Mean (SD) error was 2.3 (1.7)%. In 500 to 4174 mL FRCs, 121 (98%) of FRCs were within 5%. In 100 to 400 mL FRCs, the error was better than 7%. In vivo FRC error between tests was 10.1 (8.2)%. LCI was the most reproducible ventilation inhomogeneity index. Conclusion The lung model generates lung volumes under the conditions encountered during clinical MBW testing and enables realistic validation of MBW systems. The new N2MBW system reliably measures lung volumes and delivers reproducible LCI values.

Potentially avoidable 30-day hospital readmissions in medical patients: derivation and validation of a prediction model

IMPORTANCE Because effective interventions to reduce hospital readmissions are often expensive to implement, a score to predict potentially avoidable readmissions may help target the patients most likely to benefit. OBJECTIVE To derive and internally validate a prediction model for potentially avoidable 30-day hospital readmissions in medical patients using administrative and clinical data readily available prior to discharge. DESIGN Retrospective cohort study. SETTING Academic medical center in Boston, Massachusetts. PARTICIPANTS All patient discharges from any medical services between July 1, 2009, and June 30, 2010. MAIN OUTCOME MEASURES Potentially avoidable 30-day readmissions to 3 hospitals of the Partners HealthCare network were identified using a validated computerized algorithm based on administrative data (SQLape). A simple score was developed using multivariable logistic regression, with two-thirds of the sample randomly selected as the derivation cohort and one-third as the validation cohort. RESULTS Among 10 731 eligible discharges, 2398 discharges (22.3%) were followed by a 30-day readmission, of which 879 (8.5% of all discharges) were identified as potentially avoidable. The prediction score identified 7 independent factors, referred to as the HOSPITAL score: h emoglobin at discharge, discharge from an o ncology service, s odium level at discharge, p rocedure during the index admission, i ndex t ype of admission, number of a dmissions during the last 12 months, and l ength of stay. In the validation set, 26.7% of the patients were classified as high risk, with an estimated potentially avoidable readmission risk of 18.0% (observed, 18.2%). The HOSPITAL score had fair discriminatory power (C statistic, 0.71) and had good calibration. CONCLUSIONS AND RELEVANCE This simple prediction model identifies before discharge the risk of potentially avoidable 30-day readmission in medical patients. This score has potential to easily identify patients who may need more intensive transitional care interventions.

A nonlinear QCT-based finite element model validation study for the human femur tested in two configurations in vitro

Purpose Femoral fracture is a common medical problem in osteoporotic individuals. Bone mineral density (BMD) is the gold standard measure to evaluate fracture risk in vivo. Quantitative computed tomography (QCT)-based homogenized voxel finite element (hvFE) models have been proved to be more accurate predictors of femoral strength than BMD by adding geometrical and material properties. The aim of this study was to evaluate the ability of hvFE models in predicting femoral stiffness, strength and failure location for a large number of pairs of human femora tested in two different loading scenarios. Methods Thirty-six pairs of femora were scanned with QCT and total proximal BMD and BMC were evaluated. For each pair, one femur was positioned in one-legged stance configuration (STANCE) and the other in a sideways configuration (SIDE). Nonlinear hvFE models were generated from QCT images by reproducing the same loading configurations imposed in the experiments. For experiments and models, the structural properties (stiffness and ultimate load), the failure location and the motion of the femoral head were computed and compared. Results In both configurations, hvFE models predicted both stiffness (R2=0.82 for STANCE and R2=0.74 for SIDE) and femoral ultimate load (R2=0.80 for STANCE and R2=0.85 for SIDE) better than BMD and BMC. Moreover, the models predicted qualitatively well the failure location (66% of cases) and the motion of the femoral head. Conclusions The subject specific QCT-based nonlinear hvFE model cannot only predict femoral apparent mechanical properties better than densitometric measures, but can additionally provide useful qualitative information about failure location.

Humane Orientation as a New Cultural Dimension of the GLOBE Project: A Validation Study of the GLOBE Scale and Out-Group Humane Orientation in 25 Countries

We validate, extend, and empirically and theoretically criticize the cultural dimension of humane orientation of the project GLOBE (Global Leadership and Organizational Behavior Effectiveness Research Program). Theoretically, humane orientation is not just a one-dimensionally positive concept about being caring, altruistic, and kind to others as discussed by Kabasakal and Bodur (2004), but there is also a certain ambivalence to this concept. We suggest differentiating humane orientation toward in-group members from humane orientation toward out-group members. A multicountry construct validation study used student samples from 25 countries that were either high or low in humane orientation (N = 876) and studied their relation to the traditional GLOBE scale and other cultural-level measures (agreeableness, religiosity, authoritarianism, and welfare state score). Findings revealed a strong correlation between humane orientation and agreeableness, welfare state score, and religiosity. Out-group humane orientation proved to be the more relevant subfacet of the original humane orientation construct, suggesting that future research on humane orientation should make use of this measure instead of the vague original scale. The ambivalent character of out-group humane orientation is displayed in its positive correlation to high authoritarianism. Patriotism was used as a control variable for noncritical acceptance of one’s society but did not change the correlations. Our findings are discussed as an example of how rigid expectations and a lack of tolerance for diversity may help explain the ambivalent nature of humane orientation

Validation of middle-atmospheric campaign-based water vapour measured by the ground-based microwave radiometer MIAWARA-C

Middle atmospheric water vapour can be used as a tracer for dynamical processes. It is mainly measured by satellite instruments and ground-based microwave radiometers. Ground-based instruments capable of measuring middle-atmospheric water vapour are sparse but valuable as they complement satellite measurements, are relatively easy to maintain and have a long lifetime. MIAWARA-C is a ground-based microwave radiometer for middle-atmospheric water vapour designed for use on measurement campaigns for both atmospheric case studies and instrument intercomparisons. MIAWARA-C's retrieval version 1.1 (v1.1) is set up in a such way as to provide a consistent data set even if the instrument is operated from different locations on a campaign basis. The sensitive altitude range for v1.1 extends from 4 hPa (37 km) to 0.017 hPa (75 km). For v1.1 the estimated systematic error is approximately 10% for all altitudes. At lower altitudes it is dominated by uncertainties in the calibration, with altitude the influence of spectroscopic and temperature uncertainties increases. The estimated random error increases with altitude from 5 to 25%. MIAWARA-C measures two polarisations of the incident radiation in separate receiver channels, and can therefore provide two measurements of the same air mass with independent instrumental noise. The standard deviation of the difference between the profiles obtained from the two polarisations is in excellent agreement with the estimated random measurement error of v1.1. In this paper, the quality of v1.1 data is assessed for measurements obtained at two different locations: (1) a total of 25 months of measurements in the Arctic (Sodankylä, 67.37° N, 26.63° E) and (2) nine months of measurements at mid-latitudes (Zimmerwald, 46.88° N, 7.46° E). For both locations MIAWARA-C's profiles are compared to measurements from the satellite experiments Aura MLS and MIPAS. In addition, comparisons to ACE-FTS and SOFIE are presented for the Arctic and to the ground-based radiometer MIAWARA for the mid-latitude campaigns. In general, all intercomparisons show high correlation coefficients, confirming the ability of MIAWARA-C to monitor temporal variations of the order of days. The biases are generally below 13% and within the estimated systematic uncertainty of MIAWARA-C. No consistent wet or dry bias is identified for MIAWARA-C. In addition, comparisons to the reference instruments indicate the estimated random error of v1.1 to be a realistic measure of the random variation on the retrieved profile between 45 and 70 km.

Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches

In patients diagnosed with pharmaco-resistant epilepsy, cerebral areas responsible for seizure generation can be defined by performing implantation of intracranial electrodes. The identification of the epileptogenic zone (EZ) is based on visual inspection of the intracranial electroencephalogram (IEEG) performed by highly qualified neurophysiologists. New computer-based quantitative EEG analyses have been developed in collaboration with the signal analysis community to expedite EZ detection. The aim of the present report is to compare different signal analysis approaches developed in four different European laboratories working in close collaboration with four European Epilepsy Centers. Computer-based signal analysis methods were retrospectively applied to IEEG recordings performed in four patients undergoing pre-surgical exploration of pharmaco-resistant epilepsy. The four methods elaborated by the different teams to identify the EZ are based either on frequency analysis, on nonlinear signal analysis, on connectivity measures or on statistical parametric mapping of epileptogenicity indices. All methods converge on the identification of EZ in patients that present with fast activity at seizure onset. When traditional visual inspection was not successful in detecting EZ on IEEG, the different signal analysis methods produced highly discordant results. Quantitative analysis of IEEG recordings complement clinical evaluation by contributing to the study of epileptogenic networks during seizures. We demonstrate that the degree of sensitivity of different computer-based methods to detect the EZ in respect to visual EEG inspection depends on the specific seizure pattern.

The Career Engagement Scale: Development and validation of a measure of proactive career behaviors

Careers today increasingly require engagement in proactive career behaviors; however, there is a lack of validated measures assessing the general degree to which somebody is engaged in such career behaviors. We describe the results of six studies with six independent samples of German university students (total N = 2,854), working professionals (total N = 561), and university graduates (N = 141) that report the development and validation of the Career Engagement Scale - a measure of the degree of which somebody is proactively developing her or his career as expressed by diverse career behaviors. The studies provide supprt for measurement invariance across gender and time. In support of convergent and discriminant validity, we find that career engagement is more prevalent among working professionals than among university students and that this scale has incremental validity above several specific career behaviors regarding its relation to vocational identity clarity and career self-efficacy beliefs among students and to job and career satisfaction among employees. In support of incremental predictive validity, beyond the effects of several more specific careeer behaviors, career engagement while at university predicts higher job and career satisfaction several months later after beginning work.

Construction and first validation of the comprehensive inventory of mindfulness (CHIME)

Introduction: Measuring trait mindfulness and change in mindfulness may be a crucial prerequisite for the evaluation and further development of mindfulness based interventions for the treatment of mental disorders. This endeavour is nontrivial as current measures cover varying aspects and mindfulness and may have problems regarding validity. This presentation describes the development and validation of a questionnaire for the comprehensive assessment of mindfulness: the Comprehensive Inventory of Mindfulness Experiences (CHIME). Method: The factor structure, reliability, and validity of the CHIME were established in a community sample (N = 298) and a sample of MBSR group participants (N = 161). Results: Factor-analytical procedures supported an eight-factor structure. The structure was tested in a further confirmatory sample (N = 202). The questionnaire and its subscales exhibited good reliability (internal consistency and retest-reliability). Analysis of the measurement invariance of the single items over groups differing in age, gender, meditation experience, and symptom load pointed to the absence of systematic differences in the items' semantic understanding. Parameters reflecting construct validity, criterion validity, and incremental validity as well as change sensitivity were all at least satisfactory. Conclusions: The CHIME is a self-report measure with favorable psychometric properties based on all aspects of mindfulness that are included in current mindfulness scales. This scale may be helpful in the evaluation and further development of mindfulness based interventions.

International validation of a behavioral scale in Parkinson's disease without dementia.

The "Ardouin Scale of Behavior in Parkinson's Disease" is a new instrument specifically designed for assessing mood and behavior with a view to quantifying changes related to Parkinson's disease, to dopaminergic medication, and to non-motor fluctuations. This study was aimed at analyzing the psychometric attributes of this scale in patients with Parkinson's disease without dementia. In addition to this scale, the following measures were applied: the Unified Parkinson's Disease Rating Scale, the Montgomery and Asberg Depression Rating Scale, the Lille Apathy Rating Scale, the Bech and Rafaelsen Mania Scale, the Positive and Negative Syndrome Scale, the MacElroy Criteria, the Patrick Carnes criteria, the Hospital Anxiety and Depression Scale, and the Mini-International Neuropsychiatric Interview. Patients (n = 260) were recruited at 13 centers across four countries (France, Spain, United Kingdom, and United States). Cronbach's alpha coefficient for domains ranged from 0.69 to 0.78. Regarding test-retest reliability, the kappa coefficient for items was higher than 0.4. For inter-rater reliability, the kappa values were 0.29 to 0.81. Furthermore, most of the items from the Ardouin Scale of Behavior in Parkinson's Disease correlated with the corresponding items of the other scales, depressed mood with the Montgomery and Asberg Depression Rating Scale (ρ = 0.82); anxiety with the Hospital Anxiety and Depression Scale-anxiety (ρ = 0.56); apathy with the Lille Apathy Rating Scale (ρ = 0.60). The Ardouin Scale of Behavior in Parkinson's disease is an acceptable, reproducible, valid, and precise assessment for evaluating changes in behavior in patients with Parkinson's disease without dementia. © 2015 International Parkinson and Movement Disorder Society.

Simple measures of climate, soil properties and plant traits predict national-scale grassland soil carbon stocks

Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. Using data from an extensive national survey of English grasslands, we show that surface soil (0–7 cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. Soil C stocks in the largest pool, of intermediate particle size (50–250 μm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0·45–50 μm), was explained by soil pH and the community abundance-weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N-rich vegetation. The C stock in the small active fraction (250–4000 μm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. Synthesis and applications. Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1–100 000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

Prognostic and diagnostic value of EEG signal coupling measures in coma.

OBJECTIVE Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients. METHODS In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. RESULTS Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). CONCLUSIONS EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. SIGNIFICANCE Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches.

Development and validation of the Neuro Symptom Inventory in the primary brain tumor patient population

Symptoms has been shown to predict quality of life, treatment course and survival in solid tumor patients. Currently, no instrument exists that measures both cancer-related symptoms and the neurologic symptoms that are unique to persons with primary brain tumors (PBT). The aim of this study was to develop and validate an instrument to measure symptoms in patients who have PBT. A conceptual analysis of symptoms and symptom theories led to defining the symptoms experience as the perception of the frequency, intensity, distress, and meaning that occurs as symptoms are produced, perceived, and expressed. The M.D. Anderson Symptom Inventory (MDASI) measures both symptoms and how they interfere with daily functioning in patients with cancer, which is similar to the situational meaning defined in the analysis. A list of symptoms pertinent to the PBT population was added to the core MDASI and reviewed by a group of experts for validity. As a result, 18 items were added to the core MDASI (the MDASI-BT) for the next phase of instrument development, establishing validity and reliability through a descriptive, cross-sectional approach with PBT patients. Data were collected with a patient completed demographic data sheet, an investigator completed clinician checklist, and the MDASI-BT. Analysis evaluated the reliability and validity of the MDASI-BT in PBT patients. Data were obtained from 201 patients. The number of items was reduced to 22 by evaluation of symptom severity as well as cluster analysis. Regression analysis showed more than half (56%) of the variability in symptom severity was explained by the brain tumor module items. Factor analysis confirmed that the 22 item MDASI-BT measured six underlying constructs: (a) affective; (b) cognitive; (c) focal neurologic deficits; (d) constitutional symptoms; (e) treatment-related symptoms; and (f) gastrointestinal symptoms. The MDASI-BT was sensitive to disease severity and if the patient was hospitalized. The MDASI-BT is the first instrument to measure symptoms in PBT patients that has demonstrated reliability and validity. It is the first step in a program of research to evaluate the occurrence of symptoms and plan and evaluate interventions for PBT patients. ^