New global indicator for workers' health: mortality rate from diseases attributable to selected occupational risk factors.

Through sustainable development goals 3 and 8 and other policies, countries have committed to protect and promote workers' health by reducing the work-related burden of disease. To monitor progress on these commitments, indicators that capture the work-related burden of disease should be available for monitoring workers' health and sustainable development. The World Health Organization and the International Labour Organization estimate that only 363 283 (19%) of 1 879 890 work-related deaths globally in 2016 were due to injuries, whereas 1 516 607 (81%) deaths were due to diseases. Most monitoring systems focusing on workers' health or sustainable development, such as the global indicator framework for the sustainable development goals, include an indicator on the burden of occupational injuries. Few such systems, however, have an indicator on the burden of work-related diseases. To address this gap, we present a new global indicator: mortality rate from diseases attributable to selected occupational risk factors, by disease, risk factor, sex and age group. We outline the policy rationale of the indicator, describe its data sources and methods of calculation, and report and analyse the official indicator for 183 countries. We also provide examples of the use of the indicator in national workers' health monitoring systems and highlight the indicator's strengths and limitations. We conclude that integrating the new indicator into monitoring systems will provide more comprehensive and accurate surveillance of workers' health, and allow harmonization across global, regional and national monitoring systems. Inequalities in workers' health can be analysed and the evidence base can be improved towards more effective policy and systems on workers' health.

Par le biais des objectifs de développement durable 3 et 8 ainsi que d'autres mesures, plusieurs pays se sont engagés à protéger et promouvoir la santé des travailleurs en réduisant l'impact des maladies liées au travail. Mais pour évaluer leurs progrès en la matière, il convient de mettre en place des indicateurs estimant l'impact des maladies liées au travail afin de placer le développement durable et la santé des travailleurs sous surveillance. D'après l'Organisation mondiale de la Santé et l'Organisation internationale du Travail, seulement 363 283 (19%) des 1 879 890 décès liés au travail dans le monde en 2016 découlaient de blessures, tandis que 1 516 607 (81%) d'entre eux étaient causés par des maladies. La plupart des systèmes de surveillance qui s'intéressent à la santé des travailleurs ou au développement durable, comme le cadre mondial d'indicateurs pour les objectifs de développement durable, comportent un indicateur relatif à l'impact des accidents de travail. Cependant, rares sont ceux qui possèdent un indicateur concernant l'impact des maladies professionnelles. Pour combler cette lacune, nous dévoilons un nouvel indicateur mondial: le taux de mortalité dû aux maladies attribuables à certains facteurs de risque professionnels classé par maladie, facteur de risque, sexe et catégorie d'âge. Nous exposons le motif politique de l'indicateur, décrivons l'origine des données et les méthodes de calcul, et communiquons et analysons l'indicateur officiel pour 183 pays. Nous fournissons également des exemples de la façon dont l'indicateur peut être utilisé dans des systèmes nationaux de surveillance de la santé des travailleurs et soulignons ses forces et faiblesses. Nous concluons en affirmant que l'intégration de ce nouvel indicateur dans les systèmes de surveillance offrira un suivi plus complet et précis de la santé des travailleurs et ouvrira la voie à une harmonisation des systèmes mondiaux, nationaux et régionaux. Il est possible d'analyser les inégalités en matière de santé des travailleurs et d'en améliorer les bases factuelles afin d'établir des politiques et systèmes plus efficaces dans ce domaine.

A través de los objetivos de desarrollo sostenible 3 y 8 y de otras políticas, los países se han comprometido a proteger y promover la salud de los trabajadores reduciendo la carga de morbilidad relacionada con el trabajo. Para supervisar los avances en el cumplimiento de estos compromisos, debería disponerse de indicadores que reflejen la carga de morbilidad relacionada con el trabajo, a fin de controlar la salud de los trabajadores y el desarrollo sostenible. La Organización Mundial de la Salud y la Organización Internacional del Trabajo estiman que solo 363 283 (19%) de las 1 879 890 muertes relacionadas con el trabajo a nivel mundial en 2016 se debieron a lesiones, mientras que 1 516 607 (81%) muertes se debieron a enfermedades. La mayoría de los sistemas de vigilancia centrados en la salud de los trabajadores o el desarrollo sostenible, como el marco de indicadores mundiales para los objetivos de desarrollo sostenible, incluyen un indicador sobre la carga de las lesiones laborales. No obstante, pocos de estos sistemas cuentan con un indicador sobre la carga de las enfermedades relacionadas con el trabajo. Para subsanar esta carencia, presentamos un nuevo indicador mundial: la tasa de mortalidad por enfermedades atribuibles a factores de riesgo laborales seleccionados, por enfermedad, factor de riesgo, sexo y grupo de edad. Describimos la justificación política del indicador, describimos sus fuentes de datos y métodos de cálculo, e informamos y analizamos el indicador oficial para 183 países. También proporcionamos ejemplos del uso del indicador en los sistemas nacionales de vigilancia de la salud de los trabajadores y destacamos las ventajas y las limitaciones del indicador. Concluimos que la integración del nuevo indicador en los sistemas de vigilancia proporcionará una vigilancia más exhaustiva y precisa de la salud de los trabajadores, y permitirá la armonización entre los sistemas de vigilancia mundiales, regionales y nacionales. Se podrán analizar las desigualdades en la salud de los trabajadores y se podrá mejorar la base de evidencias para lograr políticas y sistemas más eficaces en materia de salud de los trabajadores.

Predicting Breast Cancer Events in Ductal Carcinoma In Situ (DCIS) Using Generative Adversarial Network Augmented Deep Learning Model.

Standard clinicopathological parameters (age, growth pattern, tumor size, margin status, and grade) have been shown to have limited value in predicting recurrence in ductal carcinoma in situ (DCIS) patients. Early and accurate recurrence prediction would facilitate a more aggressive treatment policy for high-risk patients (mastectomy or adjuvant radiation therapy), and simultaneously reduce over-treatment of low-risk patients. Generative adversarial networks (GAN) are a class of DL models in which two adversarial neural networks, generator and discriminator, compete with each other to generate high quality images. In this work, we have developed a deep learning (DL) classification network that predicts breast cancer events (BCEs) in DCIS patients using hematoxylin and eosin (H & E) images. The DL classification model was trained on 67 patients using image patches from the actual DCIS cores and GAN generated image patches to predict breast cancer events (BCEs). The hold-out validation dataset (n = 66) had an AUC of 0.82. Bayesian analysis further confirmed the independence of the model from classical clinicopathological parameters. DL models of H & E images may be used as a risk stratification strategy for DCIS patients to personalize therapy.

Deformable Mapping Method to Relate Lesions in Dedicated Breast CT Images to Those in Automated Breast Ultrasound and Digital Breast Tomosynthesis Images.

This work demonstrates the potential for using a deformable mapping method to register lesions between dedicated breast computed tomography (bCT) and both automated breast ultrasound (ABUS) and digital breast tomosynthesis (DBT) images (craniocaudal [CC] and mediolateral oblique [MLO] views). Two multi-modality breast phantoms with external fiducial markers attached were imaged by the three modalities. The DBT MLO view was excluded for the second phantom. The automated deformable mapping algorithm uses biomechanical modeling to determine corresponding lesions based on distances between their centers of mass (dCOM) in the deformed bCT model and the reference model (DBT or ABUS). For bCT to ABUS, the mean dCOM was 5.2 ± 2.6 mm. For bCT to DBT (CC), the mean dCOM was 5.1 ± 2.4 mm. For bCT to DBT (MLO), the mean dCOM was 4.7 ± 2.5 mm. This application could help improve a radiologist's efficiency and accuracy in breast lesion characterization, using multiple imaging modalities.

Deformable mapping using biomechanical models to relate corresponding lesions in digital breast tomosynthesis and automated breast ultrasound images.

This work investigates the application of a deformable localization/mapping method to register lesions between the digital breast tomosynthesis (DBT) craniocaudal (CC) and mediolateral oblique (MLO) views and automated breast ultrasound (ABUS) images. This method was initially validated using compressible breast phantoms. This methodology was applied to 7 patient data sets containing 9 lesions. The automated deformable mapping algorithm uses finite element modeling and analysis to determine corresponding lesions based on the distance between their centers of mass (dCOM) in the deformed DBT model and the reference ABUS model. This technique shows that location information based on external fiducial markers is helpful in the improvement of registration results. However, use of external markers are not required for deformable registration results described by this methodology. For DBT (CC view) mapped to ABUS, the mean dCOM was 14.9 ±â€¯6.8 mm based on 9 lesions using 6 markers in deformable analysis. For DBT (MLO view) mapped to ABUS, the mean dCOM was 13.7 ±â€¯6.8 mm based on 8 lesions using 6 markers in analysis. Both DBT views registered to ABUS lesions showed statistically significant improvements (p ≤ 0.05) in registration using the deformable technique in comparison to a rigid registration. Application of this methodology could help improve a radiologist's characterization and accuracy in relating corresponding lesions between DBT and ABUS image datasets, especially for cases of high breast densities and multiple masses.

A 4-channel, vector network analyzer microwave imaging prototype based on software defined radio technology.

We have implemented a prototype 4-channel transmission-based, microwave measurement system built on innovative software defined radio (SDR) technology. The system utilizes the B210 USRP SDR developed by Ettus Research that operates over a 70 MHz-6 GHz bandwidth. While B210 units are capable of being synchronized with each other via coherent reference signals, they are somewhat unreliable in this configuration and the manufacturer recommends using N200 or N210 models instead. For our system, N-series SDRs were less suitable because they are not amenable to RF shielding required for the cross-channel isolation necessary for an integrated microwave imaging system. Consequently, we have configured an external reference that overcame these limitations in a compact and robust package. Our design exploits the rapidly evolving technology being developed for the telecommunications environment for test and measurement tasks with the higher performance specifications required in medical microwave imaging applications. In a larger channel configuration, the approach is expected to provide performance comparable to commercial vector network analyzers at a fraction of the cost and in a more compact footprint.

Image Registration for Microwave Tomography of the Breast Using Priors From Nonsimultaneous Previous Magnetic Resonance Images.

Microwave imaging is a low-cost imaging method that has shown promise for breast imaging and, in particular, neoadjuvant chemotherapy monitoring. The early studies of microwave imaging in the therapy monitoring setting are encouraging. For the neoadjuvant therapy application, it would be desirable to achieve the most accurate possible characterization of the tissue properties. One method to achieve increased resolution and specificity in microwave imaging reconstruction is the use of a soft prior regularization. The objective of this study is to develop a method to use magnetic resonance (MR) images, taken in a different imaging configuration, as this soft prior. To enable the use of the MR images as a soft prior, it is necessary to register the MR images to the microwave imaging space. Registration fiducials were placed around the breast that are visible in both the MRI and with an optical scanner integrated into the microwave system. Utilizing these common registration locations, numerical algorithms have been developed to warp the original breast MR images into a geometry closely resembling that in which the breast is pendant in the microwave system.

Deformable mapping technique to correlate lesions in digital breast tomosynthesis and automated breast ultrasound images.

PURPOSE: To develop a deformable mapping technique to match corresponding lesions between digital breast tomosynthesis (DBT) and automated breast ultrasound (ABUS) images. METHODS: External fiducial markers were attached to the surface of two CIRS multi-modality compressible breast phantoms (A and B) containing multiple simulated lesions. Both phantoms were imaged with DBT (upright positioning with cranial-caudal compression) and ABUS (supine positioning with anterior-to-chest wall compression). The lesions and markers were manually segmented by three different readers. Reader segmentation similarity and reader reproducibility were assessed using Dice similarity coefficients (DSC) and distances between centers of mass (dCOM ). For deformable mapping between the modalities each reader's segmented dataset was processed with an automated deformable mapping algorithm as follows: First, Morfeus, a finite element (FE) based multi-organ deformable image registration platform, converted segmentations into triangular surface meshes. Second, Altair HyperMesh, a FE pre-processor, created base FE models for the ABUS and DBT data sets. All deformation is performed on the DBT image data; the ABUS image sets remain fixed throughout the process. Deformation was performed on the external skin contour (DBT image set) to match the external skin contour on the ABUS set, and the locations of the external markers were used to morph the skin contours to be within a user-defined distance. Third, the base DBT-FE model was deformed with the FE analysis solver, Optistruct. Deformed DBT lesions were correlated with matching lesions in the base ABUS FE model. Performance (lesion correlation) was assessed with dCOM for all corresponding lesions and lesion overlap. Analysis was performed to determine the minimum number of external fiducial markers needed to create the desired correlation and the improvement of correlation with the use of external markers. RESULTS: Average DSC for reader similarity ranged from 0.88 to 0.91 (ABUS) and 0.57 to 0.83 (DBT). Corresponding dCOM ranged from 0.20 to 0.36 mm (ABUS) and 0.11 to 1.16 mm (DBT). Lesion correlation is maximized when all corresponding markers are within a maximum distance of 5 mm. For deformable mapping of phantom A, without the use of external markers, only two of six correlated lesions showed overlap with an average lesion dCOM of 6.8 ± 2.8 mm. With use of three external fiducial markers, five of six lesions overlapped and average dCOM improved to 4.9 ± 2.4 mm. For deformable mapping of Phantom B without external markers analysis, four lesions were correlated of seven with overlap between only one of seven lesions, and an average lesion dCOM of 9.7 ± 3.5 mm. With three external markers, all seven possible lesions were correlated with overlap between four of seven lesions. The average dCOM was 8.5 ± 4.0 mm. CONCLUSION: This work demonstrates the potential for a deformable mapping technique to relate corresponding lesions in DBT and ABUS images by showing improved lesion correspondence and reduced lesion registration errors with the use of external fiducial markers. The technique should improve radiologists' characterization of breast lesions which can reduce patient callbacks, misdiagnoses and unnecessary biopsies.

Preliminary Clinical Experience with a Combined Automated Breast Ultrasound and Digital Breast Tomosynthesis System.

We analyzed the performance of a mammographically configured, automated breast ultrasound (McABUS) scanner combined with a digital breast tomosynthesis (DBT) system. The GE Invenia ultrasound system was modified for integration with GE DBT systems. Ultrasound and DBT imaging were performed in the same mammographic compression. Our small preliminary study included 13 cases, six of whom had contained invasive cancers. From analysis of these cases, current limitations and corresponding potential improvements of the system were determined. A registration analysis was performed to compare the ease of McABUS to DBT registration for this system with that of two systems designed previously. It was observed that in comparison to data from an earlier study, the McABUS-to-DBT registration alignment errors for both this system and a previously built combined system were smaller than those for a previously built standalone McABUS system.

Clinical characteristics and prognostic factors in multiple myeloma patients with light chain deposition disease.

Light chain deposition disease (LCDD) is characterized by monotypic immunoglobulin depositions which will eventually lead to loss of organ function if left untreated. While the kidney is almost always affected, the presence and degree of LCDD in other organs vary. Ten to thirty percent of LCDD patients have underlying Multiple Myeloma (MM), yet outcome and prognostic markers in this particular patient group are still lacking. Here, we analyzed 69 patients with MM and biopsy proven LCDD and report on renal and extra-renal involvement and its impact on prognosis as well as renal response depending on hematologic response. Coexisting light chain diseases such as AL amyloid and cast nephropathy were found in 30% of patients; those with LCDD and concurrent amyloid tended to have shorter survival. Cardiac involvement by LCDD was seen in one-third of our patients and was associated with shorter overall survival; such patients also had a significantly higher risk of treatment-related mortality (TRM) after stem cell transplant (SCT) compared to LCDD patients without cardiac involvement. This study highlights that MM patients with LCDD present with different clinical features compared to previously reported LCDD cohorts. Rapid initiation of treatment is necessary to prevent progressive renal disease and worse outcome. Coexisting light chain diseases and cardiac involvement are more common than previously reported and confer worse clinical outcome, emphasizing the need for careful patient careful patient evaluation and treatment selection.

Early life adversity and/or posttraumatic stress disorder severity are associated with poor diet quality, including consumption of trans fatty acids, and fewer hours of resting or sleeping in a US middle-aged population: A cross-sectional and prospective study.

BACKGROUND: Early life adversity (ELA) and post-traumatic stress disorder (PTSD) are associated with poorer psychological and physical health. Potential underlying mechanisms and mediators remain to be elucidated, and the lifestyle habits and characteristics of individuals with ELA and/or PTSD have not been fully explored. We investigated whether the presence of ELA and/or PTSD are associated with nutrition, physical activity, resting and sleeping and smoking. METHODS: A cross-sectional sample of 151 males and females (age: 45.6±3.5 years, BMI: 30.0±7.1 kg/m(2)) underwent anthropometric measurements, as well as detailed questionnaires for dietary assessment, physical activity, resting and sleeping, smoking habits and psychosocial assessments. A prospective follow-up visit of 49 individuals was performed 2.5 years later and the same outcomes were assessed. ELA and PTSD were evaluated as predictors, in addition to a variable assessing the combined presence/severity of ELA-PTSD. Data were analyzed using analysis of covariance after adjusting for several socioeconomic, psychosocial and anthropometric characteristics. RESULTS: Individuals with higher ELA or PTSD severity were found to have a poorer diet quality (DASH score: p=0.006 and p=0.003, respectively; aHEI-2010 score: ELA p=0.009), including further consumption of trans fatty acids (ELA p=0.003); the differences were significantly attenuated null after adjusting mainly for education or income and/or race. Further, individuals with higher ELA severity reported less hours of resting and sleeping (p=0.043) compared to those with zero/lower ELA severity, and the difference remained significant in the fully adjusted model indicating independence from potential confounders. When ELA and PTSD were combined, an additive effect was observed on resting and sleeping (p=0.001); results remained significant in the fully adjusted model. They also consumed more energy from trans fatty acids (p=0.017) tended to smoke more (p=0.008), and have less physical activity (PTSD p=0.024) compared to those with no or lower ELA and PTSD severity. Adjustments for sociodemographic factors and/or BMI rendered results of the above lifestyle parameters non-significant. The analysis of the prospective data showed similar trends to the cross-sectional analysis, further supporting the conclusions, although statistical significance of results was lower due to the lower number of participants. CONCLUSION: Fewer hours of resting and sleeping and poorer diet quality are linked to ELA and/or PTSD, indicating that these pathways might underlie the development of several metabolic abnormalities in individuals with ELA and/or PTSD. Differences in terms of diet quality are significantly attenuated by race and/or education and/or income, whereas differences in other lifestyle habits of individuals with and without ELA and/or PTSD, such as physical activity, are mostly explained by confounding sociodemographic variables and/or body mass index.

Attachment and the metabolic syndrome in midlife: the role of interview-based discourse patterns.

OBJECTIVE: Adult attachment discourse patterns and current family relationship quality were examined as correlates of health behaviors and number of metabolic syndrome (MetS) criteria met, and as mediators of the link between childhood adversity and these health outcomes. METHODS: A sample of 215 white/European American and black/African American adults aged 35 to 55 years were examined using a cross-sectional study design. Discourse was assessed with the Adult Attachment Interview, using coherence (a marker of attachment security), unresolved trauma/loss (a marker of disorganized cognitions related to trauma or loss), and idealization (minimizing stressful experiences and their impact) scores. Relationship quality, adverse childhood experiences, and current depressive symptoms were assessed, as were health behaviors of diet, exercise, and smoking. MetS includes obesity, elevated blood pressure, elevated fasting glucose, high triglycerides, and low high-density lipoprotein cholesterol. RESULTS: Using path analysis and including childhood adversity severity and depressive symptoms in the model, both Adult Attachment Interview coherence and unresolved trauma/loss were directly linked to the number of MetS criteria (r = 0.186 and r = 0.170, respectively). Idealization was indirectly linked to MetS through poor diet (r = 0.183). The final model explained 21% of the variance in scores for the number of MetS criteria met. CONCLUSIONS: Insecure adult attachment is associated with increased risk of MetS.

Detailed assessments of childhood adversity enhance prediction of central obesity independent of gender, race, adult psychosocial risk and health behaviors.

OBJECTIVE: This study examined whether a novel indicator of overall childhood adversity, incorporating number of adversities, severity, and chronicity, predicted central obesity beyond contributions of "modifiable" risk factors including psychosocial characteristics and health behaviors in a diverse sample of midlife adults. The study also examined whether the overall adversity score (number of adversities × severity × chronicity) better predicted obesity compared to cumulative adversity (number of adversities), a more traditional assessment of childhood adversity. MATERIALS/METHODS: 210 Black/African Americans and White/European Americans, mean age=45.8; ±3.3 years, were studied cross-sectionally. Regression analysis examined overall childhood adversity as a direct, non-modifiable risk factor for central obesity (waist-hip ratio) and body mass index (BMI), with and without adjustment for established adult psychosocial risk factors (education, employment, social functioning) and heath behavior risk factors (smoking, drinking, diet, exercise). RESULTS: Overall childhood adversity was an independent significant predictor of central obesity, and the relations between psychosocial and health risk factors and central obesity were not significant when overall adversity was in the model. Overall adversity was not a statistically significant predictor of BMI. CONCLUSIONS: Overall childhood adversity, incorporating severity and chronicity and cumulative scores, predicts central obesity beyond more contemporaneous risk factors often considered modifiable. This is consistent with early dysregulation of metabolic functioning. Findings can inform practitioners interested in the impact of childhood adversity and personalizing treatment approaches of obesity within high-risk populations. Prevention/intervention research is necessary to discover and address the underlying causes and impact of childhood adversity on metabolic functioning.

Imatinib mesylate for plexiform neurofibromas in patients with neurofibromatosis type 1: a phase 2 trial.

BACKGROUND: Plexiform neurofibromas are slow-growing chemoradiotherapy-resistant tumours arising in patients with neurofibromatosis type 1 (NF1). Currently, there are no viable therapeutic options for patients with plexiform neurofibromas that cannot be surgically removed because of their proximity to vital body structures. We undertook an open-label phase 2 trial to test whether treatment with imatinib mesylate can decrease the volume burden of clinically significant plexiform neurofibromas in patients with NF1. METHODS: Eligible patients had to be aged 3-65 years, and to have NF1 and a clinically significant plexiform neurofibroma. Patients were treated with daily oral imatinib mesylate at 220 mg/m(2) twice a day for children and 400 mg twice a day for adults for 6 months. The primary endpoint was a 20% or more reduction in plexiform size by sequential volumetric MRI imaging. Clinical data were analysed on an intention-to-treat basis; a secondary analysis was also done for those patients able to take imatinib mesylate for 6 months. This trial is registered with ClinicalTrials.gov, number NCT01673009. FINDINGS: Six of 36 patients (17%, 95% CI 6-33), enrolled on an intention-to-treat basis, had an objective response to imatinib mesylate, with a 20% or more decrease in tumour volume. Of the 23 patients who received imatinib mesylate for at least 6 months, six (26%, 95% CI 10-48) had a 20% or more decrease in volume of one or more plexiform tumours. The most common adverse events were skin rash (five patients) and oedema with weight gain (six). More serious adverse events included reversible grade 3 neutropenia (two), grade 4 hyperglycaemia (one), and grade 4 increases in aminotransferase concentrations (one). INTERPRETATION: Imatinib mesylate could be used to treat plexiform neurofibromas in patients with NF1. A multi-institutional clinical trial is warranted to confirm these results. FUNDING: Novartis Pharmaceuticals, the Indiana University Simon Cancer Centre, and the Indiana University Herman B Wells Center for Pediatric Research.