Auditing Abbreviated Breast MR Imaging: Clinical Considerations and Implications

Abbreviated breast MR (AB-MR) imaging is a relatively new breast imaging tool, which maintains diagnostic accuracy while reducing image times compared with full-protocol breast MR (FP-MR) imaging. Breast imaging audits involve calculating individual and organizational metrics, which can be compared with established benchmarks, providing a standard against which performance can be measured. Unlike FP-MR imaging, there are no established benchmarks for AB-MR imaging but studies demonstrate comparable performance for cancer detection rate, positive predictive value 3, sensitivity, and specificity with T2. We review the basics of performing an audit, including strategies to implement if benchmarks are not being met.

Expanding the utility of robotics for pancreaticoduodenectomy: a 10-year review and comparison to international benchmarks in pancreatic surgery

BACKGROUND

Robotic pancreaticoduodenectomy (RPD) is an emerging alternative to open pancreaticoduodenectomy (OPD). Although RPD offers various theoretical advantages, it is used in less than 10% of all pancreaticoduodenectomies. The aim of this study was to report our 10-year experience and compare RPD outcomes with international benchmarks for OPD.

METHODS

A retrospective review of a prospectively maintained institutional database was performed of consecutive patients who underwent RPD between January 2011 and December 2021. Patients were categorized into low-risk and high-risk groups according to the selection criteria set by the benchmark study. Their outcomes were compared to the international benchmark cut off values. Outcomes were then evaluated over time to identify improvements in practice and establish a learning curve.

RESULTS

Of 201 RPDs, 36 were low-risk and 165 high-risk patients. Compared to the OPD benchmarks, outcomes of low-risk patients were within the cutoff values. High-risk patients were outside the cutoff for blood transfusions (26% vs. ≤ 23%), overall complications (78% vs. ≤ 73%), grade I-II complications (68% vs. ≤ 62%), and readmissions (22% vs ≤ 21%). Oncologic outcomes for high-risk patients were within benchmark cutoffs. Cases at the end of the learning curve included more pancreatic cancer (42% from 17%) and fewer low-risk patients (10% from 24%) than those at the beginning. After 41 RPD there was a decline in conversion rates and operative time. Between 95 and 143 cases operative time, transfusion rates, and LOS declined significantly. Complications did not differ over time.

CONCLUSION

RPD yields results comparable to the established benchmarks in OPD in both low- and high-risk patients. Along the learning curve, RPD evolved with the inclusion of more high-risk cases while outcomes remained within benchmarks. Addition of a robotic HPB surgery fellowship did not compromise outcomes. These results suggest that RPD may be an option for high-risk patients at specialized centers.

ChampKit: A framework for rapid evaluation of deep neural networks for patch-based histopathology classification

BACKGROUND AND OBJECTIVE

Histopathology is the gold standard for diagnosis of many cancers. Recent advances in computer vision, specifically deep learning, have facilitated the analysis of histopathology images for many tasks, including the detection of immune cells and microsatellite instability. However, it remains difficult to identify optimal models and training configurations for different histopathology classification tasks due to the abundance of available architectures and the lack of systematic evaluations. Our objective in this work is to present a software tool that addresses this need and enables robust, systematic evaluation of neural network models for patch classification in histology in a light-weight, easy-to-use package for both algorithm developers and biomedical researchers.

METHODS

Here we present ChampKit (Comprehensive Histopathology Assessment of Model Predictions toolKit): an extensible, fully reproducible evaluation toolkit that is a one-stop-shop to train and evaluate deep neural networks for patch classification. ChampKit curates a broad range of public datasets. It enables training and evaluation of models supported by timm directly from the command line, without the need for users to write any code. External models are enabled through a straightforward API and minimal coding. As a result, Champkit facilitates the evaluation of existing and new models and deep learning architectures on pathology datasets, making it more accessible to the broader scientific community. To demonstrate the utility of ChampKit, we establish baseline performance for a subset of possible models that could be employed with ChampKit, focusing on several popular deep learning models, namely ResNet18, ResNet50, and R26-ViT, a hybrid vision transformer. In addition, we compare each model trained either from random weight initialization or with transfer learning from ImageNet pretrained models. For ResNet18, we also consider transfer learning from a self-supervised pretrained model.

RESULTS

The main result of this paper is the ChampKit software. Using ChampKit, we were able to systemically evaluate multiple neural networks across six datasets. We observed mixed results when evaluating the benefits of pretraining versus random intialization, with no clear benefit except in the low data regime, where transfer learning was found to be beneficial. Surprisingly, we found that transfer learning from self-supervised weights rarely improved performance, which is counter to other areas of computer vision.

CONCLUSIONS

Choosing the right model for a given digital pathology dataset is nontrivial. ChampKit provides a valuable tool to fill this gap by enabling the evaluation of hundreds of existing (or user-defined) deep learning models across a variety of pathology tasks. Source code and data for the tool are freely accessible at https://github.com/SBU-BMI/champkit.

Continual Object Detection: A review of definitions, strategies, and challenges

The field of Continual Learning investigates the ability to learn consecutive tasks without losing performance on those previously learned. The efforts of researchers have been mainly focused on incremental classification tasks. Yet, we believe that continual object detection deserves even more attention due to its vast range of applications in robotics and autonomous vehicles. This scenario is also more complex than conventional classification, given the occurrence of instances of classes that are unknown at the time but can appear in subsequent tasks as a new class to be learned, resulting in missing annotations and conflicts with the background label. In this review, we analyze the current strategies proposed to tackle the problem of class-incremental object detection. Our main contributions are: (1) a short and systematic review of the methods that propose solutions to traditional incremental object detection scenarios; (2) A comprehensive evaluation of the existing approaches using a new metric to quantify the stability and plasticity of each technique in a standard way; (3) an overview of the current trends within continual object detection and a discussion of possible future research directions.

Introducing a New High-Resolution Handwritten Digits Data Set with Writer Characteristics

The contributions in this article are two-fold. First, we introduce a new handwritten digit data set that we collected. It contains high-resolution images of handwritten digits together with various writer characteristics which are not available in the well-known MNIST database. The multiple writer characteristics gathered are a novelty of our data set and create new research opportunities. The data set is publicly available online. Second, we analyse this new data set. We begin with simple supervised tasks. We assess the predictability of the writer characteristics gathered, the effect of using some of those characteristics as predictors in classification task and the effect of higher resolution images on classification accuracy. We also explore semi-supervised applications; we can leverage the high quantity of handwritten digits data sets already existing online to improve the accuracy of various classifications task with noticeable success. Finally, we also demonstrate the generative perspective offered by this new data set; we are able to generate images that mimics the writing style of specific writers. The data set has unique and distinct features and our analysis establishes benchmarks and showcases some of the new opportunities made possible with this new data set.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42979-022-01494-2.

Benchmark datasets driving artificial intelligence development fail to capture the needs of medical professionals

Publicly accessible benchmarks that allow for assessing and comparing model performances are important drivers of progress in artificial intelligence (AI). While recent advances in AI capabilities hold the potential to transform medical practice by assisting and augmenting the cognitive processes of healthcare professionals, the coverage of clinically relevant tasks by AI benchmarks is largely unclear. Furthermore, there is a lack of systematized meta-information that allows clinical AI researchers to quickly determine accessibility, scope, content and other characteristics of datasets and benchmark datasets relevant to the clinical domain. To address these issues, we curated and released a comprehensive catalogue of datasets and benchmarks pertaining to the broad domain of clinical and biomedical natural language processing (NLP), based on a systematic review of literature and. A total of 450 NLP datasets were manually systematized and annotated with rich metadata, such as targeted tasks, clinical applicability, data types, performance metrics, accessibility and licensing information, and availability of data splits. We then compared tasks covered by AI benchmark datasets with relevant tasks that medical practitioners reported as highly desirable targets for automation in a previous empirical study. Our analysis indicates that AI benchmarks of direct clinical relevance are scarce and fail to cover most work activities that clinicians want to see addressed. In particular, tasks associated with routine documentation and patient data administration workflows are not represented despite significant associated workloads. Thus, currently available AI benchmarks are improperly aligned with desired targets for AI automation in clinical settings, and novel benchmarks should be created to fill these gaps.

The implementation of a precision case management model in a Canadian inpatient rehabilitation center: The 12-months post-implementation findings of a quality improvement project

Despite recommendations, few have reported on quality improvement initiatives to implement length of rehabilitation stay benchmarks, while actively monitoring functional outcomes. This article describes the development, implementation, and evaluation of a precision case management model across all inpatient rehabilitation client groups in a Canadian facility. To develop the length of rehabilitation-stay (LoRS) benchmarks, patient data was retrospectively analyzed. A severity specific method was used to stratify median length of stay. A target reduction on 8.6 days in LoRS was established. Functional discharge targets were also set and monitored at specific intervals via the Functional Independence Measure (FIM®). The implementation used an incremental quality improvement phased approach. Following 12-months, a statistically significant reduction in mean LoRS of 13.2 days was achieved, along with a small increase in FIM® change across all rehabilitation client groups. A similar pattern was seen across the three main client groups, where a LoRS reduction greater than the target was achieved, along with important improvements in LoRS efficiency. This study demonstrates how the implementation of a precision case management model can assist a facility in markedly reducing LoRS across inpatient groups, without compromising functional change or community discharge rates and begin its transformation to a value-based organization.

Racial/ethnic inequalities in cervical cancer screening in the United States: An outcome reclassification to better inform interventions and benchmarks

In the United states (U.S.), prevailing understanding suggests significant racial/ethnic inequalities in cervical cancer screening exist. However, recent findings elsewhere in North America indicate the magnitude of these inequalities depend on the way screening is defined: lifetime screening versus up-to-date screening. As those who have never been screened are most at risk for invasive cancer, an improved understanding of inequalities in this outcome is necessary to better inform interventions. To describe racial/ethnic inequalities in 1) never screening and 2) not being up-to-date with screening among women who have been screened at least once in their lifetime, three years (2014-2016) of the U.S. Behavioral Risk Factor Surveillance Survey were utilized to estimate cervical cancer screening prevalence ratios via Poisson regression (N = 123,070). The sample was limited to women age 21 to 65 years. Women from racial/ethnic minority groups were more likely to never have been screened in comparison to White women, particularly women of Asian descent (Prevalence Ratio (PR) = 3.8, 95% CI = 3.3-4.3). However, among women who had been screened at least once in their lifetime, an inverse association was observed between being a member of a racial/ethnic minority group and not being up-to-date with screening (e.g. PR_{asian vs white} = 0.7, 95% CI = 0.6-0.9). Physicians and public health institutions concerned with monitoring racial/ethnic inequalities should consider adding lifetime screening as a primary benchmark, as this outcome implies different intervention targets to address inequalities and the differential burden of cervical cancer.

Wrist pulse signal acquisition and analysis for disease diagnosis: A review

Pulse diagnosis (PD) plays an indispensable role in healthcare in China, India, Korea, and other Orient countries. It requires considerable training and experience to master. The results of pulse diagnosis rely heavily on the practitioner's subjective analysis, which means that the results from different physicians may be inconsistent. To overcome these drawbacks, computational pulse diagnosis (CPD) is used with advanced sensing techniques and analytical methods. Focusing on the main processes of CPD, this paper provides a systematic review of the latest advances in pulse signal acquisition, signal preprocessing, feature extraction, and signal recognition. The most relevant principles and applications are presented along with current progress. Extensive comparisons and analyses are conducted to evaluate the merits of different methods employed in CPD. While much progress has been made, a lack of datasets and benchmarks has limited the development of CPD. To address this gap and facilitate further research, we present a benchmark to evaluate different methods. We conclude with observations of the status and prospects of CPD.

Sediment toxicity data and excess simultaneously extracted metals from field-collected samples: Comparison to United States Environmental Protection Agency benchmarks

US Environmental Protection Agency (USEPA) Procedures for the Derivation of Equilibrium Partitioning Sediment Benchmarks (ESBs) for the Protection of Benthic Organisms: Metal Mixtures are based on the principle that metals toxicity to benthic organisms is determined by bioavailable metals concentrations in porewater. One ESB is based on the difference between simultaneously extracted metal (SEM) and acid volatile sulfide (AVS) concentrations in sediment (excess SEM). The excess SEM ESBs include a lower uncertainty bound, below which most samples (95%) are expected to be "nontoxic" (defined as a bioassay mortality rate ≤24%), and an upper uncertainty bound, above which most samples (95%) are expected to be "toxic" (defined as a mortality rate >24%). Samples that fall between the upper and lower bounds are classified as "uncertain." Excess SEM ESBs can, in principle, be improved by normalizing for organic carbon (OC). OC is a binding phase that reduces metals bioavailability. OC normalization should improve the accuracy of bioavailable metal concentration estimates, thus tightening uncertainty bounds. We evaluated field-collected sediments from 13 studies with excess SEM, OC, and bioassay data (n = 740). Use of the OC-normalized excess SEM benchmarks did not improve prediction accuracy. The ESB model predicts OC-normalized excess SEM exceeding the upper benchmark even when toxicity is not observed, because error in the OC normalization model increases at low OC concentrations. To minimize the likelihood of incorrectly identifying nontoxic samples as toxic, we recommend that OC normalization of excess SEM should not be considered for sediments with an OC concentration <1% and is questionable for sediments with an OC concentration of 1%-4%. Additional focused studies are needed to confirm or refine the minimum sediment OC concentrations that are applicable for reducing uncertainty in toxicity predictions due to excess SEM. Integr Environ Assess Manag 2022;18:174-186. © 2021 SETAC.

Benchmarking diagnostic laboratory performance: Survey results for Germany, Austria, and Switzerland

BACKGROUND AND AIMS

The need for patient safety through consistent diagnostic performance has increasingly been brought into focus during the last two decades. Around the globe operational efficiency of diagnostic laboratories plays a key role in satisfying this need, which has impressively been shown during the recent months of the SARS-CoV‑2 pandemic. On a global level, however, there has been a lack to collate and benchmark data for diagnostic laboratories. The goals of this study were to design and pilot a questionnaire addressing key aspects of diagnostic laboratory management.

METHODS

The questionnaire was designed using an iterative process and taking into consideration information that could be extracted from the literature, author experience and feedback from informal focus groups of laboratory professionals. The resulting tool consisted of 50 items, either relating to general information or more specifically addressing the topics of "operational performance", "integrated clinical care performance", and "financial sustainability". A limited number of laboratories were surveyed to be able to further improve the newly developed tool and motivate the global laboratory community to participate in further benchmarking activity.

RESULTS AND CONCLUSION

Altogether, 65 laboratories participated in the survey, 42 were hospital laboratories and 23 were commercial laboratories. Potential for further improvement and standardization became apparent across the board, e.g. use of IT for order management, auto-validation, or turn-around time (TAT) monitoring. Notably, a gap was identified regarding services provided to physicians, in particular "reflexive test suggestions", "proactive consultation on complex cases", and "diagnostic pathways guidance", which were only provided by about two thirds of laboratories. Concordantly, within-laboratory TAT (Lab TAT) was monitored by about 80% of respondents, while sample-to-result TAT, which is arguably the TAT most relevant to clinicians, was only monitored by 32% of respondents. Altogether, the need for stronger integration of the laboratory into the clinical care process became apparent and should be a main trajectory of future laboratory management.

Continual learning for recurrent neural networks: An empirical evaluation

Learning continuously during all model lifetime is fundamental to deploy machine learning solutions robust to drifts in the data distribution. Advances in Continual Learning (CL) with recurrent neural networks could pave the way to a large number of applications where incoming data is non stationary, like natural language processing and robotics. However, the existing body of work on the topic is still fragmented, with approaches which are application-specific and whose assessment is based on heterogeneous learning protocols and datasets. In this paper, we organize the literature on CL for sequential data processing by providing a categorization of the contributions and a review of the benchmarks. We propose two new benchmarks for CL with sequential data based on existing datasets, whose characteristics resemble real-world applications. We also provide a broad empirical evaluation of CL and Recurrent Neural Networks in class-incremental scenario, by testing their ability to mitigate forgetting with a number of different strategies which are not specific to sequential data processing. Our results highlight the key role played by the sequence length and the importance of a clear specification of the CL scenario.

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation

BACKGROUND

Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs).

RESULTS

The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (≥3 kbp) contigs, while k-mer- and blast-based tools were uniquely able to detect viruses from short (≤3 kbp) contigs. Notably, however, the performance increase of k-mer- and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to ∼5% for virome and ∼75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. For viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from ∼95% (whole genomes) down to ∼80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a best-practices workflow to curate candidate AMGs in viral genomes assembled from metagenomes.

CONCLUSION

Together, these benchmarking experiments and annotation guidelines should aid researchers seeking to best detect, classify, and characterize the myriad viruses 'hidden' in diverse sequence datasets.

The OCI-12: A syndromally valid modification of the obsessive-compulsive inventory-revised

The 18-item Obsessive-Compulsive Inventory-Revised (OCI-R) is a widely used self-report measure of Obsessive-Compulsive Disorder (OCD) symptoms, yet its factor structure does not converge with contemporary dimensional models of OCD symptoms. In addition to assessing the four core OCD dimensions, the OCI-R includes hoarding and neutralizing factors. However, since its publication, hoarding has been designated as a separate disorder, and there are concerns about the neutralizing factor's reliability and validity. The aim of this study was to evaluate a syndromally valid modification of the OCI-R. Adult samples of individuals diagnosed with OCD (n = 1087), anxiety related disorders (n = 1306), and unselected community volunteers (n = 423) completed the OCI-R and measures of anxiety and mood. Analyses excluded the 3 OCI-R hoarding items and suggested the removal of the 3 neutralizing items. Internal consistency, sensitivity and specificity to OCD clinical status, test-retest reliability, sensitivity to treatment, and convergent and discriminant validity were evaluated for the resultant 12-item scale (termed the OCI-12). The OCI-12 evidenced good to excellent psychometric properties. Clinical norms, severity benchmarks, and a clinical cutoff score were computed. In conclusion, the OCI-12 represents a syndromally valid update of the OCI-R with comparable psychometric properties and superior sensitivity and specificity.

Efficiency evaluation of Brazilian airlines operations considering the Covid-19 outbreak

In this paper we evaluate the operational efficiency of the Brazilian airlines considering the novel coronavirus Covid-19 outbreak. This novel coronavirus was first reported end of 2019 in Wuhan, China, however the powerful contamination spread among people forced the World Health Organization to characterize the Covid-19 as a pandemic in March of 2020. Here we analyze the main Brazilian airlines operations response due to lower demand because Covid-19 outbreak in first quarter of 2020 comparing with first quarter of 2019. The analysis here aims to verify the efficiency of airlines in domestic air transport market in Brazil through Multicriteria Data Envelopment Analysis (MCDEA) model. We used MCDEA to avoid limitations of classical DEA models for the case, especially the numbers of decision units and variable. In this paper we used an improvement of the MCDEA model to seek benchmarks considering a dual model all objective functions of MCDEA. The results highlight the challenges for the airlines, due to flight restriction and demand dropping. And also, the evaluation exposes the different company configuration of aircrafts age and network reconfiguration which was reflected by the efficiency difference on the period. The assessment shows the company with a better mix of aircraft models has a leverage on efficiency response due to unpredictable period as the pandemic Covid-19 outbreak.

Risk adjustment for benchmarking nursing home infection surveillance data: A narrative review

Until recently, there was no national surveillance system for monitoring infection occurrence in long-term care facilities (LTCF) in the United States. As a result, there are no national benchmarks for LTCF infection rates that can be utilized for quality improvement at the facility level. One of the major challenges in the reporting of health care-related infection data is accounting for nonmodifiable facility and patient characteristics that influence benchmarks for infection. The objectives of this paper are to review: (a) published infection rates in LTCF in the United States to assess the level of variability; (b) studies describing facility- and resident-level risk factors for infection that can be used in risk adjustment models; (c) published attempts to risk-adjust LTCF infection rates; and (d) efforts to develop models specifically for risk adjustment of infection rates in LTCF for benchmarking. It is anticipated that this review will stimulate further study of methods to risk-adjust LTCF infection rates for benchmarking that will facilitate research and public reporting.

Experience of health care at a reference centre as reported by patients and parents of children with rare conditions

BACKGROUND

Whilst diagnostic pathways for children with rare conditions have shown marked improvement, concerns remain about the care children with rare conditions receive at the level of the health care provider. There is, therefore, a need to improve our understanding of the health care received and explore the development of benchmarks that can be regularly monitored.

METHODS

Patients and parents with rare conditions at a tertiary children's hospital were approached to complete a questionnaire-based survey that enquired on their experience of clinical care. The survey explored six key themes: diagnosis; provision of information; availability of support; satisfaction with healthcare team; awareness and support for life-limiting conditions; and participation in research.

RESULTS

130 questionnaires were completed on behalf of 134 patients between 2018 and 2020. Of these, 114 (85%) had received a formal diagnosis, 5 (4%) had a suspected diagnosis and 15 (11%) were undiagnosed. Of the 114 who had received a diagnosis, 24 (20%) were diagnosed within 6 months of developing symptoms, and 22 (20%) within 1-3 years. Seventy patients (53%) reported that they were given little or no information around the time of diagnosis, whilst 81 (63%) felt they were currently well supported, mostly from family members, followed by friends, hospital services, school, other community based healthcare services and lastly, primary care. Of the 127 who were asked, 88 (69%) reported a consistent team of healthcare professionals taking overall responsibility for their care, 86 (67%) felt part of the team, 74 (58%) were satisfied with the level of knowledge of the professionals, and 86 (68%) knew who to contact regarding their condition. Of the 91 who were asked, 23 (25%) were aware their child had a life limiting condition, but only 4 (17%) were receiving specialist support for this. Of 17 who were asked about research, 4 (24%) were actively participating in research, whilst the remainder were all willing to participate in future research.

CONCLUSIONS

The survey provides a unique insight into the experience of patients and parents within a specialist centre and the benchmarks that it has revealed can be used for future improvement in services.

Understanding the Mammography Audit

Screening mammography aims to identify small, node-negative breast cancers when they are still curable while maintaining an acceptable range of false-positive recalls and biopsies. The mammography audit is a powerful tool to help radiologists understand their performance with respect to that goal. This article defines audit terms and describes how to use collected and derived data to perform a mammography audit. Accepted benchmarks are discussed as well as their applicability to radiologists and breast imaging practices in the United States. Special considerations regarding volumes and radiologist characteristics are explored, because these factors may affect audit results.

Percentile curves for the knee injury and osteoarthritis outcome score in the middle-aged Dutch population

OBJECTIVE

To improve the interpretation of the Knee injury and Osteoarthritis Outcome Score (KOOS) in individual patients, we explored associations with age, sex, BMI, history of knee injury and presence of clinical knee osteoarthritis, and developed percentile curves.

METHODS

We used cross-sectional data of middle-aged individuals from the population-based Netherlands Epidemiology of Obesity (NEO) study. Clinical knee osteoarthritis was defined using the ACR classification criteria. KOOS scores were handled according to the manual (zero = extreme problems, 100 = no problems). Patient characteristics associated with KOOS were explored using ordered logistic regression, and sex and body mass index (BMI)-specific percentile curves were developed using quantile regression with fractional polynomials. The curves were applied as a benchmark for comparison of KOOS scores of participants with knee osteoarthritis and comorbidities.

RESULTS

The population consisted of 6,643 participants (56% women, mean (SD) age 56(6) years). Population-based KOOS subscale scores (median; interquartile range) near optimum: pain (100;94-100), symptoms (96;86-100), ADL function (100;96-100), sport/recreation function (100;80-100), quality of life (100;75-100). Worse KOOS scores were observed in women and in participants with higher BMI. Clinical knee osteoarthritis was defined in 15% of participants, and was, in comparison to other patient characteristics, associated with the highest odds of worse KOOS scores. Furthermore, presence of any comorbidity and cardiovascular disease specifically, was associated with worse KOOS scores, particularly in women.

CONCLUSIONS

In the middle-aged Dutch population KOOS scores were generally good, but worse in women and with higher BMI. These percentile curves may be used as benchmarks in research and clinical practice.

Demonstrating the effectiveness of the fundamentals of robotic surgery (FRS) curriculum on the RobotiX Mentor Virtual Reality Simulation Platform

Fundamentals of robotic surgery (FRS) is a proficiency-based progression curriculum developed by robotic surgery experts from multiple specialty areas to address gaps in existing robotic surgery training curricula. The RobotiX Mentor is a virtual reality training platform for robotic surgery. Our aims were to determine if robotic surgery novices would demonstrate improved technical skills after completing FRS training on the RobotiX Mentor, and to compare the effectiveness of FRS across training platforms. An observational, pre-post design, multi-institutional rater-blinded trial was conducted at two American College of Surgeons Accredited Education Institutes-certified simulation centers. Robotic surgery novices (n = 20) were enrolled and trained to expert-derived benchmarks using FRS on the RobotiX Mentor. Participants' baseline skill was assessed before (pre-test) and after (post-test) training on an avian tissue model. Tests were video recorded and graded by blinded raters using the Global Evaluative Assessment of Robotic Skills (GEARS) and a 32-criteria psychomotor checklist. Post hoc comparisons were conducted against previously published comparator groups. On paired-samples T tests, participants demonstrated improved performance across all GEARS domains (p < 0.001 to p = 0.01) and for time (p < 0.001) and errors (p = 0.003) as measured by psychometric checklist. By ANOVA, improvement in novices' skill after FRS training on the RobotiX Mentor was not inferior to improvement reported after FRS training on previously published platforms. Completion of FRS on the RobotiX Mentor resulted in improved robotic surgery skills among novices, proving effectiveness of training. These data provide additional validity evidence for FRS and support use of the RobotiX Mentor for robotic surgery skill acquisition.

Evaluation of Cardiac Rehabilitation Performance and Initial Benchmarks for Australia: An Observational Cross-State and Territory Snapshot Study

BACKGROUND

Australia, unlike most high-income countries, does not have published benchmarks for cardiac rehabilitation (CR) delivery. This study provides cross-state data on CR delivery for initial benchmarks and assesses performance against international minimal standards.

METHODS

A prospective observational study March-May 2017 of CR programs in NSW (n=36), Tasmania (n=2) and ACT (n=1) was undertaken. Data were collected on 11 indicators (published dictionary), then classified as higher or lower performing using the UK National Audit of Cardiac Rehabilitation (NACR) criteria. Equity of access to higher performing CR was assessed using logistic regression.

RESULTS

Participants (n=2,436) had a mean age of 66.06±12.54 years, 68.9% were male, 16.2% culturally and linguistically diverse (CALD) and 2.6% Aboriginal and Torres Strait Islander peoples. At patient level, waiting time was median 15 (Interquartile range [IQR] 9-25) days, 24.3% had an assessment before starting, 41.8% on completion, a median 12 sessions (IQR 6-16) were delivered, which 59.1% completed and 75.4% were linked to ongoing care. At program level, using NACR criteria, 18.0% were classified as higher performing and ≥87.1% met waiting time criteria, however, only 20.5% met duration criteria. Evidence of inequitable access to higher performing programs was present with substantially higher odds for participants living in major cities (OR 28.11 95%CI 18.41, 44.92) and with every decade younger age (OR 1.89-2.94) and lower odds by 89.0% for principal referral hospital-based services (OR 0.11 95%CI 0.08, 0.14) and 31.0% for people having a CALD background (OR 0.69 95%CI 0.49, 0.97).

CONCLUSIONS

This study provides initial national CR performance benchmarks for quality improvement in Australia. While wait times are minimised, few programs are higher performing or met minimum duration standards. There is an urgent need to resource and support CR quality and access outside of major cities, in principal referral hospitals and for older and diverse patients.

WSES worldwide emergency general surgery formation and evaluation project

Optimal management of emergency surgical patients represents one of the major health challenges worldwide. Emergency general surgery (EGS) was identified as multidisciplinary surgery performed for traumatic and non-traumatic acute conditions during the same admission in the hospital. EGS represents the easiest viable way to provide affordable and high-quality level of care to emergency surgical and trauma patients. It may result from the association of different physicians with other specialties in a cooperative model. The World Society of Emergency Surgery (WSES) has been working on the EGS organization and implementation since its foundation believing in the need of common benchmarks for training and educational programs throughout the world. This is a plea in different languages to all World Prime Ministers and Presidents to support the creation in all nations of an organized hub-spoke system for emergency general surgery to improve standards of care and to save lives.

Toxicity of nickel to tropical freshwater and sediment biota: A critical literature review and gap analysis

More than two-thirds of the world's nickel (Ni) lateritic deposits are in tropical regions, and just less than half are within South East Asia and Melanesia (SEAM). With increasing Ni mining and processing in SEAM, environmental risk assessment tools are required to ensure sustainable development. Currently, there are no tropical-specific water or sediment quality guideline values for Ni, and the appropriateness of applying guideline values derived for temperate systems (e.g., Europe) to tropical ecosystems is unknown. Databases of Ni toxicity and toxicity tests for tropical freshwater and sediment species were compiled. Nickel toxicity data were ranked, using a quality assessment, identifying data to potentially use to derive tropical-specific Ni guideline values. There were no data for Ni toxicity in tropical freshwater sediments. For tropical freshwaters, of 163 Ni toxicity values for 40 different species, high-quality chronic data, based on measured Ni concentrations, were found for just 4 species (1 microalga, 2 macrophytes, and 1 cnidarian), all of which were relevant to SEAM. These data were insufficient to calculate tropical-specific guideline values for long-term aquatic ecosystem protection in tropical regions. For derivation of high-reliability tropical- or SEAM-specific water and sediment quality guideline values, additional research effort is required. Using gap analysis, we recommend how research gaps could be filled. Environ Toxicol Chem 2018;37:293-317. © 2017 SETAC.

Environmental quality benchmarks-the good, the bad, and the ugly

Environmental quality benchmarks (EQBs) such as water or sediment quality guidelines comprise one line of evidence for assessing the potential harm from chemicals and other stressors (physical, biological). They are useful but not perfect tools, should not always be used, and should never be used alone for final decision-making. The "good" can be designed to be situation-specific and can provide understandable scientific input to decision-makers. The "bad" includes perception that they are absolutes (i.e., definitive binary decision points), no or limited adaptability based on good science or common sense, and protection of individual organisms not populations of organisms. The "ugly" includes benchmarks based on simplistic indices (information loss, misleading results), misuse of biomarkers, and misapplication of EQBs. Other factors to be considered include the following: appropriately deriving EQBs, uncertainty, the laboratory is not the field, contaminant uptake and cause-effect, and specifics regarding sediment quality benchmarks (i.e., their specific "good," "bad," and "ugly" components). EQBs are not always needed or useful.

Benchmarking viromics: an in silico evaluation of metagenome-enabled estimates of viral community composition and diversity

Background

Viral metagenomics (viromics) is increasingly used to obtain uncultivated viral genomes, evaluate community diversity, and assess ecological hypotheses. While viromic experimental methods are relatively mature and widely accepted by the research community, robust bioinformatics standards remain to be established. Here we used in silico mock viral communities to evaluate the viromic sequence-to-ecological-inference pipeline, including (i) read pre-processing and metagenome assembly, (ii) thresholds applied to estimate viral relative abundances based on read mapping to assembled contigs, and (iii) normalization methods applied to the matrix of viral relative abundances for alpha and beta diversity estimates.

Results

Tools specifically designed for metagenomes, specifically metaSPAdes, MEGAHIT, and IDBA-UD, were the most effective at assembling viromes. Read pre-processing, such as partitioning, had virtually no impact on assembly output, but may be useful when hardware is limited. Viral populations with 2–5 × coverage typically assembled well, whereas lesser coverage led to fragmented assembly. Strain heterogeneity within populations hampered assembly, especially when strains were closely related (average nucleotide identity, or ANI ≥97%) and when the most abundant strain represented <50% of the population. Viral community composition assessments based on read recruitment were generally accurate when the following thresholds for detection were applied: (i) ≥10 kb contig lengths to define populations, (ii) coverage defined from reads mapping at ≥90% identity, and (iii) ≥75% of contig length with ≥1 × coverage. Finally, although data are limited to the most abundant viruses in a community, alpha and beta diversity patterns were robustly estimated (±10%) when comparing samples of similar sequencing depth, but more divergent (up to 80%) when sequencing depth was uneven across the dataset. In the latter cases, the use of normalization methods specifically developed for metagenomes provided the best estimates.

Conclusions

These simulations provide benchmarks for selecting analysis cut-offs and establish that an optimized sample-to-ecological-inference viromics pipeline is robust for making ecological inferences from natural viral communities. Continued development to better accessing RNA, rare, and/or diverse viral populations and improved reference viral genome availability will alleviate many of viromics remaining limitations.

Specific entrustable professional activities for undergraduate medical internships: a method compatible with the academic curriculum

BACKGROUND

Competency-based education has been considered the most important pedagogical trend in Medicine in the last two decades. In clinical contexts, competencies are implemented through Entrustable Professional Activities (EPAs) which are observable and measurable. The aim of this paper is to describe the methodology used in the design of educational tools to assess students´ competencies in clinical practice during their undergraduate internship (UI). In this paper, we present the construction of specific APROCs (Actividades Profesionales Confiables) in Surgery (S), Gynecology and Obstetrics (GO) and Family Medicine (FM) rotations with three levels of performance.

METHODS

The study considered a mixed method exploratory type design, a qualitative phase followed by a quantitative validation exercise. In the first stage data was obtained from three rotations (FM, GO and S) through focus groups about real and expected activities of medical interns. Triangulation with other sources was made to construct benchmarks. In the second stage, narrative descriptions with the three levels were validated by professors who teach the different subjects using the Delphi technique.

RESULTS

The results may be described both curricular and methodological wise. From the curricular point of view, APROCs were identified in three UI rotations within clinical contexts in Mexico City, benchmarks were developed by levels and validated by experts' consensus. In regard to methodological issues, this research contributed to the development of a strategy, following six steps, to build APROCs using mixed methods.

CONCLUSIONS

Developing benchmarks provides a regular and standardized language that helps to evaluate student's performance and define educational strategies efficiently and accurately. The university academic program was aligned with APROCs in clinical contexts to assure the acquisition of competencies by students.

Benchmarking of venous thromboembolism prophylaxis practice with ENT.UK guidelines

The aim of this study was to benchmark our guidelines of prevention of venous thromboembolism (VTE) in ENT surgical population against ENT.UK guidelines, and also to encourage healthcare providers to utilize benchmarking as an effective method of improving performance. The study design is prospective descriptive analysis. The setting of this study is tertiary referral centre (Assir Central Hospital, Abha, Saudi Arabia). In this study, we are benchmarking our practice guidelines of the prevention of VTE in the ENT surgical population against that of ENT.UK guidelines to mitigate any gaps. ENT guidelines 2010 were downloaded from the ENT.UK Website. Our guidelines were compared with the possibilities that either our performance meets or fall short of ENT.UK guidelines. Immediate corrective actions will take place if there is quality chasm between the two guidelines. ENT.UK guidelines are evidence-based and updated which may serve as role-model for adoption and benchmarking. Our guidelines were accordingly amended to contain all factors required in providing a quality service to ENT surgical patients. While not given appropriate attention, benchmarking is a useful tool in improving quality of health care. It allows learning from others' practices and experiences, and works towards closing any quality gaps. In addition, benchmarking clinical outcomes is critical for quality improvement and informing decisions concerning service provision. It is recommended to be included on the list of quality improvement methods of healthcare services.

When does a functional correctly describe both the structure and the energy of the transition state?

Requiring that several properties are well reproduced is a severe test on density functional approximations. This can be assessed through the estimation of joint and conditional success probabilities. An example is provided for a small set of molecules, for properties characterizing the transition states (geometries and energies).

Coral benchmarks in the center of biodiversity

There is an urgent need to quantify coral reef benchmarks that assess changes and recovery rates through time and serve as goals for management. Yet, few studies have identified benchmarks for hard coral cover and diversity in the center of marine diversity. In this study, we estimated coral cover and generic diversity benchmarks on the Tubbataha reefs, the largest and best-enforced no-take marine protected area in the Philippines. The shallow (2-6m) reef slopes of Tubbataha were monitored annually, from 2012 to 2015, using hierarchical sampling. Mean coral cover was 34% (σ±1.7) and generic diversity was 18 (σ±0.9) per 75m by 25m station. The southeastern leeward slopes supported on average 56% coral cover, whereas the northeastern windward slopes supported 30%, and the western slopes supported 18% coral cover. Generic diversity was more spatially homogeneous than coral cover.

The Effects of Waiting for Treatment: A Meta-Analysis of Waitlist Control Groups in Randomized Controlled Trials for Social Anxiety Disorder

Social anxiety disorder (SAD) is a highly prevalent mental disorder. However, little is known about how SAD changes in subjects who do not receive treatment. Waitlist control groups (WLCGs) are frequently included in randomized controlled trials (RCTs) on the treatment of mental disorders. Data from WLCGs are of value as they provide information on the untreated short-term course of a disorder and may serve as disorder-specific norms of change (benchmarks) against which treatment outcomes of SAD can be compared. Thus, we performed a meta-analysis focusing on the effects occurring in WLCGs of RCTs for SAD. Our study was conducted along the PRISMA guidelines. Thirty RCTs (total n = 2460) comprising 30 WLCGs and 47 treatment groups were included. Mean waiting time was 10.6 weeks. The pooled effect of waiting on SAD measures was g = 0.128 (95% CI: 0.057-0.199). Effects regarding other forms of anxiety, depression and functioning were of similarly small size. In contrast, change in the treatment groups was large, both within (g = 0.887) and between groups (g = 0.860). Our results show that for SAD, changes occurring in WLCGs of RCTs are small. The findings may serve as benchmarks in pilot studies of a new treatment or as an additional comparison in studies comparing two active treatments. For psychotherapy research in general, the small effect sizes found in WLCGs confirm that testing a treatment against a waiting list is not a very strict test. Further research on WLCGs in specific mental disorders is required, for example examining the expectancies of patients randomized to waiting. Copyright © 2016 John Wiley & Sons, Ltd.

KEY PRACTITIONER MESSAGE

In clinical practice, patients suffering from a mental disorder often have to wait for treatment. By analyzing data from waitlist control groups we can gain estimates of symptom change that occur during waiting. It could be seen that waiting for treatment only results in a negligible effect. Thus, in the short-term (i.e., 10.6 weeks) time is no healer in social anxiety disorder. Our results are similar to previous meta-analyses on the effects of waiting in other disorders, e.g., depression and posttraumatic stress disorder.

Towards a barrier height benchmark set for biologically relevant systems

We have collected computed barrier heights and reaction energies (and associated model structures) for five enzymes from studies published by Himo and co-workers. Using this data, obtained at the B3LYP/6- 311+G(2d,2p)[LANL2DZ]//B3LYP/6-31G(d,p) level of theory, we then benchmark PM6, PM7, PM7-TS, and DFTB3 and discuss the influence of system size, bulk solvation, and geometry re-optimization on the error. The mean absolute differences (MADs) observed for these five enzyme model systems are similar to those observed for PM6 and PM7 for smaller systems (10-15 kcal/mol), while DFTB results in a MAD that is significantly lower (6 kcal/mol). The MADs for PMx and DFTB3 are each dominated by large errors for a single system and if the system is disregarded the MADs fall to 4-5 kcal/mol. Overall, results for the condensed phase are neither more or less accurate relative to B3LYP than those in the gas phase. With the exception of PM7-TS, the MAD for small and large structural models are very similar, with a maximum deviation of 3 kcal/mol for PM6. Geometry optimization with PM6 shows that for one system this method predicts a different mechanism compared to B3LYP/6-31G(d,p). For the remaining systems, geometry optimization of the large structural model increases the MAD relative to single points, by 2.5 and 1.8 kcal/mol for barriers and reaction energies. For the small structural model, the corresponding MADs decrease by 0.4 and 1.2 kcal/mol, respectively. However, despite these small changes, significant changes in the structures are observed for some systems, such as proton transfer and hydrogen bonding rearrangements. The paper represents the first step in the process of creating a benchmark set of barriers computed for systems that are relatively large and representative of enzymatic reactions, a considerable challenge for any one research group but possible through a concerted effort by the community. We end by outlining steps needed to expand and improve the data set and how other researchers can contribute to the process.

18. Preparedness process

This Chapter provides a layout for the development, implementation, and evaluation of interventions designed to enhance/augment the levels of preparedness of the public health and medical care aspects of disasters. The preparedness framework is provided for the analysis of the preparedness process and consists of 17 steps: (1) hazard and risk identification; (2) vulnerabilities, historical perspectives and predictions; (3) selection of hazard(s) to address; (4) selection of indicators; (5) standards and benchmarks for preparedness; (6) current status; (7) identification of preparedness needs; (8) strategic planning; (9) selection of intervention; (10) operational planning; (11) implementation; (12) conclusion/finalise: end points; (13) documentation of effects; (14) transition, maintenance, sustainability; (15) evaluation; and (16) feedback. At any time in this algorithm the process may be terminated by or after consultation with the coordination and control centre. Each of these processes is described in detail. In addition, attention is directed to the coordination and control centre during planning, preparedness, and evaluations of preparedness.

Measuring Quality in Pediatric Endoscopy

Measuring quality in endoscopy includes the assessment of appropriateness of a procedure and the skill with which it is performed. High-quality pediatric endoscopy is safe and efficient, used effectively to make proper diagnoses, is useful for excluding other diagnoses, minimizes adverse events, and is accompanied by appropriate documentation from beginning through end of the procedure. There are no standard quality metrics for pediatric endoscopy, but proposed candidates are both process and outcomes oriented. Both are likely to be used in the near future to increase transparency about patient outcomes, as well as to influence payments for the procedure.

Benchmarks for ethically credible partnerships between industry and academic health centers: beyond disclosure of financial conflicts of interest

Relationships between industry and university-based researchers have been commonplace for decades and have received notable attention concerning the conflicts of interest these relationships may harbor. While new efforts are being made to update conflict of interest policies and make industry relationships with academia more transparent, the development of broader institutional partnerships between industry and academic health centers challenges the efficacy of current policy to effectively manage these innovative partnerships. In this paper, we argue that existing strategies to reduce conflicts of interest are not sufficient to address the emerging models of industry-academic partnerships because they focus too narrowly on financial matters and are not comprehensive enough to mitigate all ethical risk. Moreover, conflict-of-interest strategies are not designed to promote best practices nor the scientific and social benefits of academic-industry collaboration. We propose a framework of principles and benchmarks for "ethically credible partnerships" between industry and academic health centers and describe how this framework may provide a practical and comprehensive approach for designing and evaluating such partnerships.

Early Detection of Lung Cancer Using Nano-Nose - A Review

Lung cancer is one of the malignancies causing deaths worldwide. The yet to be developed non-invasive diagnostic techniques, are a challenge for early detection of cancer before it progresses to its later stages. The currently available diagnostic methods are expensive or invasive, and are not fit for general screening purposes. Early identification not only helps in detecting primary cancer, but also in treating its secondaries; which creates a need for easily applicable tests to screen individuals at risk. A detailed review of the various screening methods, including the latest trend of breath analysis using gold nanoparticles, to identify cancer at its early stage, are studied here. The VOC based breath biomarkers are used to analyze the exhaled breath of the patients. These biomarkers are utilized by Chemiresistors coated with gold nanoparticles, which are found to be the most suited technique for early detection of lung cancer. This technique is highly accurate and is relatively easy to operate and was tested on smokers and non-smokers. This review also gives as an outline of the fabrication and working of the device Na-Nose. The Chemiresistors coated with Gold nanoparticles, show a great potential in being an non-invasive and cost-effective diagnostic technique for early detection of lung cancer.

How to learn about gene function: text-mining or ontologies?

As the amount of genome information increases rapidly, there is a correspondingly greater need for methods that provide accurate and automated annotation of gene function. For example, many high-throughput technologies--e.g., next-generation sequencing--are being used today to generate lists of genes associated with specific conditions. However, their functional interpretation remains a challenge and many tools exist trying to characterize the function of gene-lists. Such systems rely typically in enrichment analysis and aim to give a quick insight into the underlying biology by presenting it in a form of a summary-report. While the load of annotation may be alleviated by such computational approaches, the main challenge in modern annotation remains to develop a systems form of analysis in which a pipeline can effectively analyze gene-lists quickly and identify aggregated annotations through computerized resources. In this article we survey some of the many such tools and methods that have been developed to automatically interpret the biological functions underlying gene-lists. We overview current functional annotation aspects from the perspective of their epistemology (i.e., the underlying theories used to organize information about gene function into a body of verified and documented knowledge) and find that most of the currently used functional annotation methods fall broadly into one of two categories: they are based either on 'known' formally-structured ontology annotations created by 'experts' (e.g., the GO terms used to describe the function of Entrez Gene entries), or--perhaps more adventurously--on annotations inferred from literature (e.g., many text-mining methods use computer-aided reasoning to acquire knowledge represented in natural languages). Overall however, deriving detailed and accurate insight from such gene lists remains a challenging task, and improved methods are called for. In particular, future methods need to (1) provide more holistic insight into the underlying molecular systems; (2) provide better follow-up experimental testing and treatment options, and (3) better manage gene lists derived from organisms that are not well-studied. We discuss some promising approaches that may help achieve these advances, especially the use of extended dictionaries of biomedical concepts and molecular mechanisms, as well as greater use of annotation benchmarks.

13. Operational planning for a specific intervention

Every intervention must follow an operational plan. Operational plans delineate actions required to meet an objective that is part of the strategic plan (overarching goal). Operational plans dictate the critical pathways for the interventions that will be followed during and following the implementation of the intervention. Operational plans include: (1) an introduction and brief situation report; (2) an overview of the task(s), objectives, and the overarching goal to be addressed; (3) the methods that will be employed; (4) planning factors; (5) the resources that will be required including personnel, equipment, and supplies; (6) timelines, benchmarks, and milestones including their respective indicators, startup time, end point, and estimates of the time required for completion; (7) the administrative structure to be employed; (8) an operating budget; (9) the strategy for acquiring the funding required; (10) roles and responsibilities of the personnel including position descriptions and the competencies required of the personnel (skill sets); (11) mechanisms for monitoring the progress including the indicators that will be employed, (12) safety, including health of the personnel, required immunisations, accommodations, and reporting structure; (13) self-sufficiency; and (14) reporting and accounting. There are many generic items in an operational plan that can be used in successive plans. Without a detailed operational plan, interventions are doomed to probable failure and can profoundly negatively impact other projects operational in the area.

Post-mortem evidence of doxylamine in toxicological analyses

BACKGROUND

Doxylamine (DA) is widely available in pharmacies without prescription and can be used in suicidal intention because of its sedative and anticholinergic properties. Research of literature shows that only a few publications deal with post-mortem evidence of DA and its interpretation during toxicological examination.

MATERIAL AND METHODS

In this study, all cases with a positive detection of DA during toxicological analyses with high-performance liquid chromatography in the time period 2000 to 2010 at the Institute of Legal Medicine and Forensic Sciences in Berlin, Germany were retrospectively analysed and interpreted, taking into account police investigations, autopsy results and toxicological analyses.

RESULTS

In total, 22 cases with DA intoxications were discovered (♂=16/♀=6, age-at-death range 17 to 90years). Maximum blood concentration was measured at 77.5μg/mL. Cause of death was due to DA intoxication in eight suicide cases; seven of those were combined intoxications (DA and other substances, particularly diphenhydramine). During the evaluated time period no monointoxications with DA were discovered.

CONCLUSION

Benchmarks published in past literature are meant as orientation during evaluation of post-mortem DA evidence. These should not be used as absolute values and need to be interpreted individually in each case. Post-mortem redistribution needs to be considered as a main factor in alteration of DA concentration measurement. Furthermore, proof of DA ingestion found in gastric content should only be interpreted quantitatively due to unreliable calculation of the ingested amount. In conclusion, a variety of factors, such as the time period between time of death and the time of the first toxicological analysis, the condition of the body and the findings at autopsy, must also be critically considered.

Depollution benchmarks for capacitors, batteries and printed wiring boards from waste electrical and electronic equipment (WEEE)

The article compiles and analyses sample data for toxic components removed from waste electronic and electrical equipment (WEEE) from more than 30 recycling companies in Switzerland over the past ten years. According to European and Swiss legislation, toxic components like batteries, capacitors and printed wiring boards have to be removed from WEEE. The control bodies of the Swiss take back schemes have been monitoring the activities of WEEE recyclers in Switzerland for about 15 years. All recyclers have to provide annual mass balance data for every year of operation. From this data, percentage shares of removed batteries and capacitors are calculated in relation to the amount of each respective WEEE category treated. A rationale is developed, why such an indicator should not be calculated for printed wiring boards. The distributions of these de-pollution indicators are analysed and their suitability for defining lower threshold values and benchmarks for the depollution of WEEE is discussed. Recommendations for benchmarks and threshold values for the removal of capacitors and batteries are given.