Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial

BACKGROUND

Sodium-glucose co-transporter-2 (SGLT2) inhibitors reduce progression of chronic kidney disease and the risk of cardiovascular morbidity and mortality in a wide range of patients. However, their effects on kidney disease progression in some patients with chronic kidney disease are unclear because few clinical kidney outcomes occurred among such patients in the completed trials. In particular, some guidelines stratify their level of recommendation about who should be treated with SGLT2 inhibitors based on diabetes status and albuminuria. We aimed to assess the effects of empagliflozin on progression of chronic kidney disease both overall and among specific types of participants in the EMPA-KIDNEY trial.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA), and included individuals aged 18 years or older with an estimated glomerular filtration rate (eGFR) of 20 to less than 45 mL/min per 1·73 m2, or with an eGFR of 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher. We explored the effects of 10 mg oral empagliflozin once daily versus placebo on the annualised rate of change in estimated glomerular filtration rate (eGFR slope), a tertiary outcome. We studied the acute slope (from randomisation to 2 months) and chronic slope (from 2 months onwards) separately, using shared parameter models to estimate the latter. Analyses were done in all randomly assigned participants by intention to treat. EMPA-KIDNEY is registered at ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and then followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroups of eGFR included 2282 (34·5%) participants with an eGFR of less than 30 mL/min per 1·73 m2, 2928 (44·3%) with an eGFR of 30 to less than 45 mL/min per 1·73 m2, and 1399 (21·2%) with an eGFR 45 mL/min per 1·73 m2 or higher. Prespecified subgroups of uACR included 1328 (20·1%) with a uACR of less than 30 mg/g, 1864 (28·2%) with a uACR of 30 to 300 mg/g, and 3417 (51·7%) with a uACR of more than 300 mg/g. Overall, allocation to empagliflozin caused an acute 2·12 mL/min per 1·73 m2 (95% CI 1·83-2·41) reduction in eGFR, equivalent to a 6% (5-6) dip in the first 2 months. After this, it halved the chronic slope from -2·75 to -1·37 mL/min per 1·73 m2 per year (relative difference 50%, 95% CI 42-58). The absolute and relative benefits of empagliflozin on the magnitude of the chronic slope varied significantly depending on diabetes status and baseline levels of eGFR and uACR. In particular, the absolute difference in chronic slopes was lower in patients with lower baseline uACR, but because this group progressed more slowly than those with higher uACR, this translated to a larger relative difference in chronic slopes in this group (86% [36-136] reduction in the chronic slope among those with baseline uACR <30 mg/g compared with a 29% [19-38] reduction for those with baseline uACR ≥2000 mg/g; ptrend<0·0001).

INTERPRETATION

Empagliflozin slowed the rate of progression of chronic kidney disease among all types of participant in the EMPA-KIDNEY trial, including those with little albuminuria. Albuminuria alone should not be used to determine whether to treat with an SGLT2 inhibitor.

FUNDING

Boehringer Ingelheim and Eli Lilly.

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

BACKGROUND

The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1).

INTERPRETATION

In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease.

FUNDING

Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.

Skin deformation analysis for pre-operative planning of DIEAP flap reconstruction surgery

Deep inferior epigastric artery perforator (DIEAP) flap reconstruction surgeries can potentially benefit from augmented reality (AR) in the context of surgery planning and outcomes improvement. Although three-dimensional (3D) models help visualize and map the perforators, the anchorage of the models to the patient's body during surgery does not consider eventual skin deformation from the moment of computed tomography angiography (CTA) data acquisition until the position of the patient while in surgery. In this work, we compared the 3D deformation registration from supine arms down (CTA position) to supine with arms at 90° degrees (surgical position), estimating the patient's skin deformation. We processed the data sets of 20 volunteers with a 3D rigid registration tool and performed a descriptive statistical analysis and statistical inference. With 2.45 mm of root mean square and 2.89 mm of standard deviation, results include 30% cases of deformation above 3 mm and 15% above 4 mm. Pose transformation deformation indicates that 3D surface data from the CTA scan position differs from data acquired in loco at the surgical table. Such results indicate that research should be conducted to construct accurate 3D models using CTA data to display on the patient, while considering projection errors when using AR technology.

Augmented Reality in Breast Surgery Education

Introduction

Augmented reality (AR) has demonstrated a potentially wide range of benefits and educational applications in the virtual health ecosystem. The concept of real-time data acquisition, machine learning-aided processing, and visualization is a foreseen ambition to leverage AR applications in the healthcare sector. This breakthrough with immersive technologies like AR, mixed reality, virtual reality, or extended reality will hopefully initiate a new surgical era: that of the use of the so-called surgical metaverse.

Methods

This paper focuses on the future use of AR in breast surgery education describing two potential applications (surgical remote telementoring and impalpable breast cancer localization using AR), along with the technical needs to make it possible.

Conclusion

Surgical telementoring and impalpable tumors noninvasive localization are two examples that can have success in the future provided the improvements in both data transformation and infrastructures are capable to overcome the current challenges and limitations.

Correction: Effectiveness of Secondary Risk-Reducing Strategies in Patients With Unilateral Breast Cancer With Pathogenic Variants of BRCA1 and BRCA2 Subjected to Breast-Conserving Surgery: Evidence-Based Simulation Study

[This corrects the article DOI: .].

Effectiveness of Secondary Risk-Reducing Strategies in Patients With Unilateral Breast Cancer With Pathogenic Variants of BRCA1 and BRCA2 Subjected to Breast-Conserving Surgery: Evidence-Based Simulation Study

BACKGROUND

Approximately 62% of patients with breast cancer with a pathogenic variant (BRCA1 or BRCA2) undergo primary breast-conserving therapy.

OBJECTIVE

The study aims to develop a personalized risk management decision support tool for carriers of a pathogenic variant (BRCA1 or BRCA2) who underwent breast-conserving therapy for unilateral early-stage breast cancer.

METHODS

We developed a Bayesian network model of a hypothetical cohort of carriers of BRCA1 or BRCA2 diagnosed with stage I/II unilateral breast cancer and treated with breast-conserving treatment who underwent subsequent second primary cancer risk-reducing strategies. Using event dependencies structured according to expert knowledge and conditional probabilities obtained from published evidence, we predicted the 40-year overall survival rate of different risk-reducing strategies for 144 cohorts of women defined by the type of pathogenic variants (BRCA1 or BRCA2), age at primary breast cancer diagnosis, breast cancer subtype, stage of primary breast cancer, and presence or absence of adjuvant chemotherapy.

RESULTS

Absence of adjuvant chemotherapy was the most powerful factor that was linked to a dramatic decline in survival. There was a negligible decline in the mortality in patients with triple-negative breast cancer, who received no chemotherapy and underwent any secondary risk-reducing strategy, compared with surveillance. The potential survival benefit from any risk-reducing strategy was more modest in patients with triple-negative breast cancer who received chemotherapy compared with patients with luminal breast cancer. However, most patients with triple-negative breast cancer in stage I benefited from bilateral risk-reducing mastectomy and risk-reducing salpingo-oophorectomy or just risk-reducing salpingo-oophorectomy. Most patients with luminal stage I/II unilateral breast cancer benefited from bilateral risk-reducing mastectomy and risk-reducing salpingo-oophorectomy. The impact of risk-reducing salpingo-oophorectomy in patients with luminal breast cancer in stage I/II increased with age. Most older patients with the BRCA1 and BRCA2 pathogenic variants in exons 12-24/25 with luminal breast cancer may gain a similar survival benefit from other risk-reducing strategies or surveillance.

CONCLUSIONS

Our study showed that it is mandatory to consider the complex interplay between the types of BRCA1 and BRCA2 pathogenic variants, age at primary breast cancer diagnosis, breast cancer subtype and stage, and received systemic treatment. As no prospective study results are available at the moment, our simulation model, which will integrate a decision support system in the near future, could facilitate the conversation between the health care provider and patient and help to weigh all the options for risk-reducing strategies leading to a more balanced decision.

Making Bipedal Robot Experiments Reproducible and Comparable: The Eurobench Software Approach

This study describes the software methodology designed for systematic benchmarking of bipedal systems through the computation of performance indicators from data collected during an experimentation stage. Under the umbrella of the European project Eurobench, we collected approximately 30 protocols with related testbeds and scoring algorithms, aiming at characterizing the performances of humanoids, exoskeletons, and/or prosthesis under different conditions. The main challenge addressed in this study concerns the standardization of the scoring process to permit a systematic benchmark of the experiments. The complexity of this process is mainly due to the lack of consistency in how to store and organize experimental data, how to define the input and output of benchmarking algorithms, and how to implement these algorithms. We propose a simple but efficient methodology for preparing scoring algorithms, to ensure reproducibility and replicability of results. This methodology mainly constrains the interface of the software and enables the engineer to develop his/her metric in his/her favorite language. Continuous integration and deployment tools are then used to verify the replicability of the software and to generate an executable instance independent of the language through dockerization. This article presents this methodology and points at all the metrics and documentation repositories designed with this policy in Eurobench. Applying this approach to other protocols and metrics would ease the reproduction, replication, and comparison of experiments.

Targeted Axillary Dissection after Chemotherapy: Feasibility Study with Clip and Carbon Dye Tattoo - Neotarget Trial

Background

Axillary staging in patients with complete response after neoadjuvant chemotherapy (NAC) is still controversial. Our objective was to test tattoo alone and subsequentially tattoo plus clip as markers in the targeted axillary dissection of ycN0 patients.

Methods

Prospective cohort of cT1-T3, cN1 (proven histologically), M0 patients scheduled to receive NAC. Exclusion criteria were lobular histology, prior axillary surgery, and clinical N2/3. In cohort 1 this positive node (Neotarget node) was tattooed at diagnosis. If ycN0, a targeted axillary dissection was performed. After an interim analysis with negative results we changed the protocol in order to do a double marking procedure (Cohort 2): the positive node was clipped at diagnosis and after NAC a tattoo was done before surgery.

Results

Thirteen patients in Cohort 1 and 18 patients in Cohort 2. Failure to identify the Neotarget node with multiple nodes retrieved in 9/13 (69%) of Cohort 1 patients. Also in 5/13 (38%) of Cohort 1 patients and 3/18 (17%) of Cohort 2 there was a failure to clearly identify tattooed nodes. In Cohort 2, clip identification by surgical specimen radiography allowed the identification of the tagged node in 17/18 (94,4%) of cases. The concordance between the clipped node and sentinel nodes was 16/18 (89%).

Conclusions

The introduction of double marking by clipping the metastatic node and verifying their removal by surgical specimen radiography, using carbon ink as a tracer, allowed the identification of the metastatic node in 94% of cases, with a simple, reproducible, and easy-to-implement targeted axillary dissection procedure.

The global approach to rehabilitation following an osteoporotic fragility fracture: A review of the rehabilitation working group of the International Osteoporosis Foundation (IOF) committee of scientific advisors

PURPOSE

To conduct a review of the current state of the evidence for rehabilitation strategies post-fragility fracture.

METHODS

Narrative review conducted by the Rehabilitation Working Group of the International Osteoporosis Foundation Committee of Scientific Advisors characterizing the range of rehabilitation modalities instrumental for the management of fragility fractures.

RESULTS

Multi-modal exercise post-fragility fracture to the spine and hip is strongly recommended to reduce pain, improve physical function, and improve quality of life. Outpatient physiotherapy post-hip fracture has a stronger evidence base than outpatient physiotherapy post-vertebral fracture. Appropriate nutritional care after fragility fracture provides a large range of improvement in morbidity and mortality. Education increases understanding of osteoporosis which in turn increases utilization of other rehabilitation services. Education may improve other health outcomes such as pain and increase a patient's ability for self-advocacy.

CONCLUSION

Rehabilitation interventions are inter-reliant, and research investigating the interaction of exercise, nutrition, and other multi-modal therapies may increase the relevance of rehabilitation research to clinical care.

Abstract OT1-04-04: AXSANA - EUBREAST 3 (axillary surgery after neoadjuvant treatment): An international prospective multicenter cohort study of the EUBREAST study group to evaluate different surgical methods of axillary staging (sentinel lymph node biopsy, targeted axillary dissection, axillary dissection) in clinically node-positive breast cancer patients treated with neoadjuvant chemotherapy (NCT04373655)

Background The optimal surgical staging procedure of the axilla in patients who convert from a clinically positive (cN+) to a clinically negative node status (ycN0) through neoadjuvant chemotherapy is still controversial. Widely diverse techniques such as full Axillary Lymph Node Dissection (ALND), Targeted Axillary Dissection (TAD), Targeted Lymph Node Biopsy (TLNB) and Sentinel Lymph Node Biopsy alone (SLNB) are given preference in different international guidelines. So far, no comparative data on the oncological outcome or the morbidity of the different procedures are available. Further research is needed to safely de-escalate the extent of axillary surgery in this patient group. Trial design The AXSANA study is an international prospective cohort study including cN+ patients converting to ycN0 status and treated with different axillary staging techniques according to the standard at their treating institution. The study is initiated by the EUBREAST network. The trial includes patients with cT1-4c tumors, who present initially with axillary lymph node metastasis and are scheduled for neoadjuvant chemotherapy. According to an amendment in 2020 the inclusion of patients with highly suspicious nodes without minimally invasive biopsy is allowed. All patients converting to ycN0 status undergo follow-up for 5 years irrespectively of the ypN status. Primary endpoints: Invasive disease-free survival, axillary recurrence rate and health-related quality of life (HRQoL). HRQoL are evaluated using four standardized questionnaires (EORTC QLQ-C 30, EORTC QLQ BR 23, Lymph ICF and SOC-13) at baseline and after 1, 3 and 5 years after surgery. Secondary endpoints are the feasibility and performance of different axillary staging techniques (detection rate, number of removed lymph nodes and association with complications, arm morbidity and quality of life, operating time and use of clinical and economic resources); impact of learning curve, and the detailed mapping of surgical and oncological treatment standards in different countries. The impact on different regional treatment strategies (radiotherapy, ALND) in patients with ypN0(i+), ypN1(mi) and ypN1 is assessed. Current status of the study: On June 30th 157 study sites from 15 countries are open for recruitment (Austria 2, Czech Republic 1, Finland 1, Germany 112, Greece 3, Italy 1, Norway 1, Poland 3, Portugal 5, Romania 2, Russia 1, Sweden 4, Switzerland 4, Spain 6, Turkey 11). 620 patients have been included in the study. Among patients who converted to ycN0 status, 144 have been scheduled for ALND, 157 for TAD and 49 for SLNB. The study is still open for further international study sites. Funding: AGO-B, Claudia-von Schilling Foundation, Ehmann Foundation, AWOgyn, Merit Medical, Endomagnetics, Mammotome Target accrual: 3000 patients worldwide

Citation Format: Thorsten Kühn, Steffi Hartmann, Elmar Stickeler, Jana de Boniface, Oreste Gentilini, Sarah Fröhlich, Franziska Ruf, Marc Thill, Michael Hauptmann, Guldeniz Karadeniz Cakmak, Isabel Rubio, Maria Luisa Gasparri, Michaelis Kontos, Eduard-Alexandru Bonci, Laura Niinikoski, Rosa Di Micco, Dawid Murawa, David Pinto, Florentia Peintinger, Christine Solbach, Matilda Appelgren, Jens-Uwe Blohmer, Michael Weigel, Gabriele Kaltenecker, Michael Schrauder, Janine Simons, Marjolein Smidt, Ellen Schlichting, Lukas Dostalek, Alexander Sergeevich Emelyanov, Elisabeth Thiemann, Semra Gunay, Sybille Loibl, Maggie Banys-Paluchowski. AXSANA - EUBREAST 3 (axillary surgery after neoadjuvant treatment): An international prospective multicenter cohort study of the EUBREAST study group to evaluate different surgical methods of axillary staging (sentinel lymph node biopsy, targeted axillary dissection, axillary dissection) in clinically node-positive breast cancer patients treated with neoadjuvant chemotherapy (NCT04373655) [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr OT1-04-04.

Recent advances in language & knowledge engineering

Language & Knowledge Engineering is essential for the successfully development of artificial intelligence. The technologies proposed in international forums are meant to improve all areas of our daily life whether it is related to production industries, social communities, government, education, or something else. We consider very important to reveal the recent advances Intelligent and Fuzzy Systems applied to Language & Knowledge Engineering because they are the base for the society of tomorrow. Thus, the aim of this special issue of Journal of Intelligent and Fuzzy Systems is to present a collection of papers that cover recent research results on the two wide topics: language and knowledge engineering. Even if the special issue is structured into these two general topics, we have covered specific themes such as the following ones: Natural Language Processing, Knowledge engineering, Pattern recognition, Artificial Intelligence and Language, Information Processing, Machine Learning Applied to Text Processing, Image and Text Classification, Multimodal data analysis, sentiment analysis, etc.

3D Breast Volume Estimation

INTRODUCTION

Breast volume estimation is considered crucial for breast cancer surgery planning. A single, easy, and reproducible method to estimate breast volume is not available. This study aims to evaluate, in patients proposed for mastectomy, the accuracy of the calculation of breast volume from a low-cost 3D surface scan (Microsoft Kinect) compared to the breast MRI and water displacement technique.

MATERIAL AND METHODS

Patients with a Tis/T1-T3 breast cancer proposed for mastectomy between July 2015 and March 2017 were assessed for inclusion in the study. Breast volume calculations were performed using a 3D surface scan and the breast MRI and water displacement technique. Agreement between volumes obtained with both methods was assessed with the Spearman and Pearson correlation coefficients.

RESULTS

Eighteen patients with invasive breast cancer were included in the study and submitted to mastectomy. The level of agreement of the 3D breast volume compared to surgical specimens and breast MRI volumes was evaluated. For mastectomy specimen volume, an average (standard deviation) of 0.823 (0.027) and 0.875 (0.026) was obtained for the Pearson and Spearman correlations, respectively. With respect to MRI annotation, we obtained 0.828 (0.038) and 0.715 (0.018).

DISCUSSION

Although values obtained by both methodologies still differ, the strong linear correlation coefficient suggests that 3D breast volume measurement using a low-cost surface scan device is feasible and can approximate both the MRI breast volume and mastectomy specimen with sufficient accuracy.

CONCLUSION

3D breast volume measurement using a depth-sensor low-cost surface scan device is feasible and can parallel MRI breast and mastectomy specimen volumes with enough accuracy. Differences between methods need further development to reach clinical applicability. A possible approach could be the fusion of breast MRI and the 3D surface scan to harmonize anatomic limits and improve volume delimitation.

Surgical Management of the Axilla in Clinically Node-Positive Breast Cancer Patients Converting to Clinical Node Negativity through Neoadjuvant Chemotherapy: Current Status, Knowledge Gaps, and Rationale for the EUBREAST-03 AXSANA Study

In the last two decades, surgical methods for axillary staging in breast cancer patients have become less extensive, and full axillary lymph node dissection (ALND) is confined to selected patients. In initially node-positive patients undergoing neoadjuvant chemotherapy, however, the optimal management remains unclear. Current guidelines vary widely, endorsing different strategies. We performed a literature review on axillary staging strategies and their place in international recommendations. This overview defines knowledge gaps associated with specific procedures, summarizes currently ongoing clinical trials that address these unsolved issues, and provides the rationale for further research. While some guidelines have already implemented surgical de-escalation, replacing ALND with, e.g., sentinel lymph node biopsy (SLNB) or targeted axillary dissection (TAD) in cN+ patients converting to clinical node negativity, others recommend ALND. Numerous techniques are in use for tagging lymph node metastasis, but many questions regarding the marking technique, i.e., the optimal time for marker placement and the number of marked nodes, remain unanswered. The optimal number of SLNs to be excised also remains a matter of debate. Data on oncological safety and quality of life following different staging procedures are lacking. These results provide the rationale for the multinational prospective cohort study AXSANA initiated by EUBREAST, which started enrollment in June 2020 and aims at recruiting 3000 patients in 20 countries (NCT04373655; Funded by AGO-B, Claudia von Schilling Foundation for Breast Cancer Research, AWOgyn, EndoMag, Mammotome, and MeritMedical).

Breast cancer surgery with augmented reality

Introduction: Innovations in 3D spatial technology and augmented reality imaging driven by digital high-tech industrial science have accelerated experimental advances in breast cancer imaging and the development of medical procedures aimed to reduce invasiveness. Presentation of case: A 57-year-old post-menopausal woman presented with screen-detected left-sided breast cancer. After undergoing all staging and pre-operative studies the patient was proposed for conservative breast surgery with tumor localization. During surgery, an experimental digital and non-invasive intra-operative localization method with augmented reality was compared with the standard pre-operative localization with carbon tattooing (institutional protocol). The breast surgeon wearing an augmented reality headset (Hololens) was able to visualize the tumor location projection inside the patient’s left breast in the usual supine position. Discussion: This work describes, to our knowledge, the first experimental test with a digital non-invasive method for intra-operative breast cancer localization using augmented reality to guide breast conservative surgery. In this case, a successful overlap of the previous standard pre-operative marks with carbon tattooing and tumor visualization inside the patient’s breast with augmented reality was obtained. Conclusion: Breast cancer conservative guided surgery with augmented reality can pave the way for a digital non-invasive method for intra-operative tumor localization.

A novel structure for online surgical undergraduate teaching during the COVID-19 pandemic

BACKGROUND

The Covid-19 pandemic necessitated the delivery of online higher education. Online learning is a novel experience for medical education in Sri Lanka. A novel approach to undergraduate surgical learning was taken up in an attempt to improve the interest amongst the students in clinical practice while maximizing the limited contact time.

METHOD

Online learning activity was designed involving medical students from all stages and multi consultant panel discussions. The discussions were designed to cover each topic from basic sciences to high-level clinical management in an attempt to stimulate the student interest in clinical medicine. Online meeting platform with free to use basic plan and a social media platform were used in combination to communicate with the students. The student feedback was periodically assessed for individual topics as well as for general outcome. Lickert scales and numeric scales were used to acquire student agreement on the desired learning outcomes.

RESULTS

A total of 1047 student responses for 7 questionnaires were analysed. During a 6-week period, 24 surgical topics were discussed with 51 contact hours. Eighty-seven per cent definitely agreed (highest agreement) with the statement 'students benefitted from the discussions'. Over 95% have either participated for all or most sessions. A majority of the respondents (83.4%) 'definitely agreed' that the discussions helped to improve their clinical sense. Of the total respondents, 79.3% definitely agreed that the discussions helped to build an interest in clinical medicine. Around 90% agreed that both exam-oriented and clinical practice-oriented topics were highly important and relevant. Most widely raised concerns were the poor Internet connectivity and limitation of access to the meeting platform.

CONCLUSION

Online teaching with a novel structure is feasible and effective in a resource-limited setting. Students agree that it could improve clinical interest while meeting the expected learning outcomes.

Probabilistic vs deep learning based approaches for narrow domain NER in Spanish

This work presents an experimental study on the task of Named Entity Recognition (NER) for a narrow domain in Spanish language. This study considers two approaches commonly used in this kind of problem, namely, a Conditional Random Fields (CRF) model and Recurrent Neural Network (RNN). For the latter, we employed a bidirectional Long Short-Term Memory with ELMO’s pre-trained word embeddings for Spanish. The comparison between the probabilistic model and the deep learning model was carried out in two collections, the Spanish dataset from CoNLL-2002 considering four classes under the IOB tagging schema, and a Mexican Spanish news dataset with seventeen classes under IOBES schema. The paper presents an analysis about the scalability, robustness, and common errors of both models. This analysis indicates in general that the BiLSTM-ELMo model is more suitable than the CRF model when there is “enough” training data, and also that it is more scalable, as its performance was not significantly affected in the incremental experiments (by adding one class at a time). On the other hand, results indicate that the CRF model is more adequate for scenarios having small training datasets and many classes.

Measuring interdisciplinarity of research articles: An analysis of inter-relatedness of different parameters

With evolution of knowledge disciplines and cross fertilization of ideas, research outputs reported as scientific papers are now becoming more and more interdisciplinary. An interdisciplinary research work usually involves ideas and approaches from multiple disciplines of knowledge applied to solve a specific problem. In many cases the interdisciplinary areas eventually emerge as full-fledged disciplines. In the last two decades, several approaches have been proposed to measure the Interdisciplinarity of a scientific article, such as propositions based on authorship, references, set of keywords etc. Among all these approaches, reference-set based approach is most widely used. The diversity of knowledge in the reference set has been measured with three parameters, namely variety, balance, and disparity. Different studies tried to combine these measures in one way or other to propose an aggregate measure of interdisciplinarity, called integrated diversity. However, there is a lack of understanding on inter-relations between these parameters. This paper tries to look into inter-relatedness between the three parameters by analytical study on an important interdisciplinary research area, Internet of Things (IoT). Research articles in IoT, as obtained from Web of Science for the year 2018 have been analyzed to compute the three measures and understand their inter-relatedness. Results obtained show that variety and balance are negatively correlated, variety and disparity do not show a stable relatedness and balance and disparity are negatively correlated. Further, the integrated diversity measure is negatively correlated with variety and weakly positively correlated with balance and disparity. The results imply that the composite integrated diversity measure may not be a suitably constructed composite measure of interdisciplinarity.

Sentiment analysis in Nepali: Exploring machine learning and lexicon-based approaches

In recent times, sentiment analysis research has achieved tremendous impetus on English textual data, however, a very less amount of research has been focused on Nepali textual data. This work is focused towards Nepali textual data. We have explored machine learning approaches and proposed a lexicon-based approach using linguistic features and lexical resources to perform sentiment analysis for tweets written in Nepali language. This lexicon-based approach, first pre-process the tweet, locate the opinion-oriented features and then compute the sentiment polarity of tweet. We have investigated both conventional machine learning models (Multinomial Naïve Bayes (NB), Decision Tree, Support Vector Machine (SVM) and logistic regression) and deep learning models (Convolution Neural Network (CNN), Long Short-Term Memory (LSTM) and CNN-LSTM) for sentiment analysis of Nepali text. These machine learning models and lexicon-based approach have been evaluated on tweet dataset related to Nepal Earthquake 2015 and Nepal blockade 2015. Lexicon based approach has outperformed than conventional machine learning models. Deep learning models have outperformed than conventional machine learning models and lexicon-based approach. We have also created Nepali SentiWordNet and Nepali SenticNet sentiment lexicon from existing English language resources as by-product.

Measuring semantic similarity of documents with weighted cosine and fuzzy logic

Currently, the semantic analysis is used by different fields, such as information retrieval, the biomedical domain, and natural language processing. The primary focus of this research work is on using semantic methods, the cosine similarity algorithm, and fuzzy logic to improve the matching of documents. The algorithms were applied to plain texts in this case CVs (resumes) and job descriptions. Synsets of WordNet were used to enrich the semantic similarity methods such as the Wu-Palmer Similarity (WUP), Leacock-Chodorow similarity (LCH), and path similarity (hypernym/hyponym). Additionally, keyword extraction was used to create a postings list where keywords were weighted. The task of recruiting new personnel in the companies that publish job descriptions and reciprocally finding a company when workers publish their resumes is discussed in this research work. The creation of a new gold standard was required to achieve a comparison of the proposed methods. A web application was designed to match the documents manually, creating the new gold standard. Thereby the new gold standard confirming benefits of enriching the cosine algorithm semantically. Finally, the results were compared with the new gold standard to check the efficiency of the new methods proposed. The measures used for the analysis were precision, recall, and f-measure, concluding that the cosine similarity weighted semantically can be used to get better similarity scores.

K-means based method for overlapping document clustering

Overlapping clustering algorithms have shown to be effective for clustering documents. However, the current overlapping document clustering algorithms produce a big number of clusters, which make them little useful for the user. Therefore, in this paper, we propose a k-means based method for overlapping document clustering, which allows to specify by the user the number of groups to be built. Our experiments with different corpora show that our proposal allows obtaining better results in terms of FBcubed than other recent works for overlapping document clustering reported in the literature.

Revisiting subject classification in academic databases: A comparison of the classification accuracy of Web of Science, Scopus & Dimensions

Classification of research articles into different subject areas is an extremely important task in bibliometric analysis and information retrieval. There are primarily two kinds of subject classification approaches used in different academic databases: journal-based (aka source-level) and article-based (aka publication-level). The two popular academic databases- Web of Science and Scopus- use journal-based subject classification scheme for articles, which assigns articles into a subject based on the subject category assigned to the journal in which they are published. On the other hand, the recently introduced Dimensions database is the first large academic database that uses article-based subject classification scheme that assigns the article to a subject category based on its contents. Though the subject classification schemes of Web of Science have been compared in several studies, no research studies have been done on comparison of the article-based and journal-based subject classification systems in different academic databases. This paper aims to compare the accuracy of subject classification system of the three popular academic databases: Web of Science, Scopus and Dimensions through a large-scale user-based study. Results show that the commonly held belief of superiority of article-based subject classification over the journal-based subject classification scheme does not hold at least at the moment, as Web of Science appears to have the most accurate subject classification.

Automatic Generation of Dialogues based on Grammatical Inference and the use of a Knowledge Base

In this work, we present a model for the automatic generation of written dialogues, through the use of grammatical inference. This model allows the automatic recognition of grammars from a set dialogues employed as a training set. The inferred grammars are then used to generate templates of responses within the dialogues. The final objective is to apply this model in a specific domain dialogue system that answers questions in Spanish with the use of a knowledge base. The experiments carried out have been performend using the DIHANA project corpus which contains dialogues written in Spanish about schedules and prices of a rail system.

Using automatic constructed thesauri instead of dictionaries in the verbal phraseological units validation task

Automatic validation of compositionality vs non-compositionality is a very challenging problem in NLP. A very small number of papers in literature report results in this particular problem. Recently, some new approaches have arised with respect to this particular linguistic task. One of these approaches that have called our attention is based on what authors call “lexical domain”. In this paper, we analyze the use of Pointwise Mutual Information for constructing thesauri on the fly, which can be further employed instead of dictionaries for determining whether or not a given phraseological unit is compositional or not. The experimental results carried out in this paper show that this dissimilarity measure (PMI), can effectively be used when determining compositionality of a given verbal phraseological unit. Moreover, we show that the use of thesauri improves the results obtained in comparison with those experiments employing dictionaries, highlighting the use of self-constructed lexical resources which are, in fact, taking advantage of the same vocabulary of the target dataset.

Correction to: Algorithm for the management of patients at low, high and very high risk of osteoporotic fractures

The article 'Algorithm for the management of patients at low, high and very high risk of osteoporotic fractures',written by J. A. Kanis, was originally published Online First without Open Access. After publication in volume [#], issue [#] and page [#-#], the author decided to opt for Open Choice and to make the article an Open Access publication.

Automatic detection of perforators for microsurgical reconstruction

The deep inferior epigastric perforator (DIEP) is the most commonly used free flap in mastectomy reconstruction. Preoperative imaging techniques are routinely used to detect location, diameter and course of perforators, with direct intervention from the imaging team, who subsequently draw a chart that will help surgeons choosing the best vascular support for the reconstruction. In this work, the feasibility of using a computer software to support the preoperative planning of 40 patients proposed for breast reconstruction with a DIEP flap is evaluated for the first time. Blood vessel centreline extraction and local characterization algorithms are applied to identify perforators and compared with the manual mapping, aiming to reduce the time spent by the imaging team, as well as the inherent subjectivity to the task. Comparing with the measures taken during surgery, the software calibre estimates were worse for vessels smaller than 1.5 mm (P = 6e-4) but better for the remaining ones (P = 2e-3). Regarding vessel location, the vertical component of the software output was significantly different from the manual measure (P = 0.02), nonetheless that was irrelevant during surgery as errors in the order of 2-3 mm do not have impact in the dissection step. Our trials support that a reduction of the time spent is achievable using the automatic tool (about 2 h/case). The introduction of artificial intelligence in clinical practice intends to simplify the work of health professionals and to provide better outcomes to patients. This pilot study paves the way for a success story.

The Music of the Hattons

The core of the historical collection of printed and manuscript music at Christ Church, Oxford derives from a generous bequest in the year 1710 by the late dean of the college, Henry Aldrich. Generosity of other donors is not in question, but Aldrich was more than primus inter pares. An almost contemporary bequest by Richard Goodson senior pales in comparison: printed books from before 1670 (for example) that were contributed by him number barely one-fifteenth of those from the Aldrich bequest. The means whereby Aldrich amassed his musical treasures were lost to direct investigation through the destruction of his personal papers at his express request. It is the aim of this essay to show the extent of evidence for a new claim on the origins of a large part of the collection: that Aldrich acquired shortly after the year 1670 a musical library built up by the first Baron Hatton of Kirby on the basis of his own father's collection. By correlating printed and manuscript contents, it will be shown that a further group of more widely scattered manuscripts was copied for use by Hatton's musicians, and can thus be considered as directly or indirectly dependent on his patronage.

Algorithm for the management of patients at low, high and very high risk of osteoporotic fractures

Guidance is provided in an international setting on the assessment and specific treatment of postmenopausal women at low, high and very high risk of fragility fractures.

INTRODUCTION

The International Osteoporosis Foundation and European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis published guidance for the diagnosis and management of osteoporosis in 2019. This manuscript seeks to apply this in an international setting, taking additional account of further categorisation of increased risk of fracture, which may inform choice of therapeutic approach.

METHODS

Clinical perspective and updated literature search.

RESULTS

The following areas are reviewed: categorisation of fracture risk and general pharmacological management of osteoporosis.

CONCLUSIONS

A platform is provided on which specific guidelines can be developed for national use to characterise fracture risk and direct interventions.

Lactic Acid Fermentation of Pomegranate Juice as a Tool to Improve Antioxidant Activity

An increasing consumer demand for pomegranate has been globally observed, mainly thanks to the scientific evidence related to its functional and health-promoting features. Pomegranate fruits from twenty accessions identified in Southeastern Italy were characterized according to morphological and chemical features. Juices extracted from pomegranate fruits were fermented with selected Lactobacillus plantarum PU1 and the antioxidant activity investigated. Whey was added to juices to promote the microbial growth. Fermentation led to the increase of the radical scavenging activity (up to 40%) and significant inhibition of the linoleic acid peroxidation. The three fermented juices showing the highest antioxidant activity, and the corresponding unfermented controls, were further characterized. In detail, the cytotoxicity and the protective role toward artificially induced oxidative stress were determined on murine fibroblasts Balb 3T3 through the determination of the viability and the intracellular ROS (reactive oxygen species) scavenging activity (RSA). RSA reached values of ca. 70% in fermented juices, being ca. 40% higher than the unfermented and control samples. Phenols compounds of the pomegranate juices obtained from accessions "Bitonto Piscina," "Sanrà nero," and "Wonderful (reference cultivar) were analyzed through ultrahigh pressure liquid chromatography coupled with mass spectrometry, showing that a marked increase (up to 60%) of the ellagitannins derivatives occurred during fermentation. Sensory analysis showed suitability of the fermented juices to be used as beverage and food ingredient.