Outcome Prediction for SARS-CoV-2 Patients Using Machine Learning Modeling of Clinical, Radiological, and Radiomic Features Derived from Chest CT Images

Featured Application The present study demonstrates that semi-automatic segmentation enables the identification of regions of interest affected by SARS-CoV-2 infection for the extraction of prognostic features from chest CT scans without suffering from the inter-operator variability typical of segmentation, hence offering a valuable and informative second opinion. Machine Learning methods allow identification of the prognostic features potentially reusable for the early detection and management of other similar diseases. (1) Background: Chest Computed Tomography (CT) has been proposed as a non-invasive method for confirming the diagnosis of SARS-CoV-2 patients using radiomic features (RFs) and baseline clinical data. The performance of Machine Learning (ML) methods using RFs derived from semi-automatically segmented lungs in chest CT images was investigated regarding the ability to predict the mortality of SARS-CoV-2 patients. (2) Methods: A total of 179 RFs extracted from 436 chest CT images of SARS-CoV-2 patients, and 8 clinical and 6 radiological variables, were used to train and evaluate three ML methods (Least Absolute Shrinkage and Selection Operator [LASSO] regularized regression, Random Forest Classifier [RFC], and the Fully connected Neural Network [FcNN]) for their ability to predict mortality using the Area Under the Curve (AUC) of Receiver Operator characteristic (ROC) Curves. These three groups of variables were used separately and together as input for constructing and comparing the final performance of ML models. (3) Results: All the ML models using only RFs achieved an informative level regarding predictive ability, outperforming radiological assessment, without however reaching the performance obtained with ML based on clinical variables. The LASSO regularized regression and the FcNN performed equally, both being superior to the RFC. (4) Conclusions: Radiomic features based on semi-automatically segmented CT images and ML approaches can aid in identifying patients with a high risk of mortality, allowing a fast, objective, and generalizable method for improving prognostic assessment by providing a second expert opinion that outperforms human evaluation

Possible Seasonality of Clostridium difficile in Retail Meat, Canada

We previously reported Clostridium difficile in 20% of retail meat in Canada, which raised concerns about potential foodborne transmissibility. Here, we studied the genetic diversity of C. difficile in retail meats, using a broad Canadian sampling infrastructure and 3 culture methods. We found 6.1% prevalence and indications of possible seasonality (highest prevalence in winter)

Infrared conductivity of a d_{x^2-y^2}-wave superconductor with impurity and spin-fluctuation scattering

Calculations are presented of the in-plane far-infrared conductivity of a d_{x^2-y^2}-wave superconductor, incorporating elastic scattering due to impurities and inelastic scattering due to spin fluctuations. The impurity scattering is modeled by short-range potential scattering with arbitrary phase shift, while scattering due to spin fluctuations is calculated within a weak-coupling Hubbard model picture. The conductivity is characterized by a low-temperature residual Drude feature whose height and weight are controlled by impurity scattering, as well as a broad peak centered at 4 Delta_0 arising from clean-limit inelastic processes. Results are in qualitative agreement with experiment despite missing spectral weight at high energies.Comment: 29 pages (11 tar-compressed-uuencoded Postscript figures), REVTeX 3.0 with epsf macro

Seven features of safety in maternity units: a framework based on multisite ethnography and stakeholder consultation

Background: Reducing avoidable harm in maternity services is a priority globally. As well as learning from mistakes, it is important to produce rigorous descriptions of ‘what good looks like’. Objective: We aimed to characterise features of safety in maternity units and to generate a plain language framework that could be used to guide learning and improvement. Methods: We conducted a multisite ethnography involving 401 hours of non-participant observations 33 semistructured interviews with staff across six maternity units, and a stakeholder consultation involving 65 semistructured telephone interviews and one focus group. Results: We identified seven features of safety in maternity units and summarised them into a framework, named For Us (For Unit Safety). The features include: (1) commitment to safety and improvement at all levels, with everyone involved; (2) technical competence, supported by formal training and informal learning; (3) teamwork, cooperation and positive working relationships; (4) constant reinforcing of safe, ethical and respectful behaviours; (5) multiple problem-sensing systems, used as basis of action; (6) systems and processes designed for safety, and regularly reviewed and optimised; (7) effective coordination and ability to mobilise quickly. These features appear to have a synergistic character, such that each feature is necessary but not sufficient on its own: the features operate in concert through multiple forms of feedback and amplification. Conclusions: This large qualitative study has enabled the generation of a new plain language framework—For Us—that identifies the behaviours and practices that appear to be features of safe care in hospital-based maternity units

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Conservative treatment and radiological follow-up in a case of pneumatosis intestinalis associated with enteral tube feeding

Pneumatosis Intestinalis (PI) is a rare radiological finding and is defined as the presence of extra- luminal gas within the intestinal wall. PI can be distinguished in a benign form and a life-threatening form, burdened with high mortality. The correct management of PI must always take into account patient's history, his clinical context, laboratory test results and radiological findings, in order to administrate a proper therapy and avoid unnecessary surgical intervention. The pathogenesis of primary PI is still unknown and several theories have been proposed. Here, we report the case of a man with a previous severe traumatic brain injury who developed a transitory PI secondary to the enteral nutrition through a tube feeding, conservatively treated and underwent a radiological follow- up. Our report strengthens the relationship with enteral tube feeding and PI suggesting that any disaccharide used as pharmacological excipient or sweetener in the formulations for enteral tube feeding can potentially promote PI development, especially if administered in large quantities and in particular predisposing conditions. For this reason, the correct management of PI must always take into account patient's history, his clinical context, laboratory test results and radiological findings, in order to achieve a clear comprehension of its aetiology and administrate a proper therapy, avoiding unnecessary and potentially harmful surgery

Onychoscopy with red light for vascular pattern identification: a study of 33 patients

Background: Nail dermoscopy (onychoscopy) during physical examination assists in correct diagnosis. Often further magnifications are necessary for an effective differential diagnosis. With the addition of a red light to the dermoscope, important vascular features can be visualized. Objective: To describe common features observed at onychoscopy with a new device that combines the regular white light with the red light illumination, demonstrating that it is useful for diagnosis of nail disorders. Methods: We enrolled 33 consecutive patients referred to the Nail Diseases Dermatology Unit of the University of Modena and Reggio Emilia and to the Outpatient Consultation for Nail Disease of the Dermatology Unit of the University of Bologna. Patients were assessed with a standard hand-held dermoscope and at the red light dermoscope. Dermoscopic images were collected. Results: The new prototype was used during daily clinical practice and allowed a more accurate visualization of some details that classic onychoscopy can miss. In particular, with the help of the red light it was possible to better visualize nail lesions that were characterized by some kind of colour change or vascular alterations. Conclusion: The new device of red light for vascular pattern onychoscopy can be a new investigation method to observe nail alterations, especially due to vascular pattern, even with low magnification, without the necessity to use higher resolutions

Demonstrating trustworthiness when collecting and sharing genomic data: public views across 22 countries

Background: Public trust is central to the collection of genomic and health data and the sustainability of genomic research. To merit trust, those involved in collecting and sharing data need to demonstrate they are trustworthy. However, it is unclear what measures are most likely to demonstrate this. Methods: We analyse the ‘Your DNA, Your Say’ online survey of public perspectives on genomic data sharing including responses from 36,268 individuals across 22 low-, middle- and high-income countries, gathered in 15 languages. We examine how participants perceived the relative value of measures to demonstrate the trustworthiness of those using donated DNA and/or medical information. We examine between-country variation and present a consolidated ranking of measures. Results: Providing transparent information about who will benefit from data access was the most important measure to increase trust, endorsed by more than 50% of participants across 20 of 22 countries. It was followed by the option to withdraw data and transparency about who is using data and why. Variation was found for the importance of measures, notably information about sanctions for misuse of data—endorsed by 5% in India but almost 60% in Japan. A clustering analysis suggests alignment between some countries in the assessment of specific measures, such as the UK and Canada, Spain and Mexico and Portugal and Brazil. China and Russia are less closely aligned with other countries in terms of the value of the measures presented. Conclusions: Our findings highlight the importance of transparency about data use and about the goals and potential benefits associated with data sharing, including to whom such benefits accrue. They show that members of the public value knowing what benefits accrue from the use of data. The study highlights the importance of locally sensitive measures to increase trust as genomic data sharing continues globally