Linzagolix therapy versus a placebo in patients with endometriosis-associated pain: a prospective, randomized, double-blind, Phase 3 study (EDELWEISS 3).

STUDY QUESTION: Does linzagolix administered orally once daily for up to 3 months at a dose of 75 mg alone or 200 mg in combination with add-back therapy (ABT) (1.0 mg estradiol; 0.5 mg norethindrone acetate, also known as norethisterone acetate [NETA]) demonstrate better efficacy than placebo in the management of endometriosis-related dysmenorrhea and non-menstrual pelvic pain? SUMMARY ANSWER: Combining 200 mg linzagolix with ABT was found to significantly reduce dysmenorrhea and non-menstrual pelvic pain at 3 months of therapy, while a daily dose of 75 mg linzagolix yielded a significant decrease only in dysmenorrhea at 3 months. WHAT IS KNOWN ALREADY?: A previously published Phase 2, dose-finding study reported that at a dose of 200 mg daily, linzagolix promotes full suppression of estradiol secretion to serum levels below 20 pg/ml and noted that the addition of ABT may be needed to manage hypoestrogenic side effects. At lower doses (75 mg and 100 mg/day), linzagolix maintains estradiol values within the target range of 20-60 pg/ml, which could be ideal to alleviate symptoms linked to endometriosis. STUDY DESIGN, SIZE, DURATION: EDELWEISS 3 was a multicenter, prospective, randomized, placebo-controlled, double-blind, double-dummy Phase 3 study to evaluate the safety and efficacy of linzagolix for the treatment of moderate-to-severe endometriosis-associated pain. Treatment was administered orally once daily for up to 6 months. PARTICIPANTS/MATERIALS, SETTING, METHODS: In the EDELWEISS 3 trial, 486 subjects with moderate-to-severe endometriosis-associated pain were randomized at a 1:1:1 ratio to one of the three study groups: placebo, 75 mg linzagolix alone or 200 mg linzagolix in association with ABT. Pain was measured daily on a verbal rating scale and recorded in an electronic diary. MAIN RESULTS AND THE ROLE OF CHANCE: At 3 months, the daily 200 mg linzagolix dose with ABT met the primary efficacy objective, showing clinically meaningful and statistically significant reductions in dysmenorrhea and non-menstrual pelvic pain, with stable or decreased use of analgesics. The proportion of responders for dysmenorrhea in the 200 mg linzagolix with ABT group was 72.9% compared with 23.5% in the placebo group (P < 0.001), while the rates of responders for non-menstrual pelvic pain were 47.3% and 30.9% (P = 0.007), respectively. The 75 mg linzagolix daily dose demonstrated a clinically meaningful and statistically significant reduction in dysmenorrhea versus placebo at 3 months. The proportion of responders for dysmenorrhea in the 75 mg linzagolix group was 44.0% compared with 23.5% in the placebo group (P < 0.001). Although the 75 mg dose showed a trend toward reduction in non-menstrual pelvic pain at 3 months relative to the placebo, it was not statistically significant (P = 0.279). Significant improvements in dyschezia and overall pelvic pain were observed in both linzagolix groups when compared to placebo. Small improvements in dyspareunia scores were observed in both linzagolix groups but they were not significant. In both groups, hypoestrogenic effects were mild, with low rates of hot flushes and bone density loss of <1%. A daily dose of 200 mg linzagolix with ABT or 75 mg linzagolix alone was found to significantly reduce dysmenorrhea and non-menstrual pelvic pain also at 6 months of therapy. LIMITATIONS, REASONS FOR CAUTION: Efficacy was compared between linzagolix groups and placebo; however, it would be useful to have results from comparative studies with estro-progestogens or progestogens. It will be important to ascertain whether gonadotropin-releasing hormone antagonists have significant benefits over traditional first-line medications. WIDER IMPLICATIONS OF THE FINDINGS: Linzagolix administered orally once daily at a dose of 200 mg in combination with add-back therapy (ABT) demonstrated better efficacy and safety than placebo in the management of moderate-to-severe endometriosis-associated pain. The quality of life was improved and the risks of bone loss and vasomotor symptoms were minimized due to the ABT. The 75 mg dose alone could be suitable for chronic treatment of endometriosis-associated pain without the need for concomitant hormonal ABT, but further research is needed to confirm this. If confirmed, it would offer a viable option for women who do not want to wish to have ABT or for whom it is contraindicated. STUDY FUNDING/COMPETING INTEREST(S): Funding for the EDELWEISS 3 study was provided by ObsEva (Geneva, Switzerland). Analysis of data and manuscript writing were partially supported by ObsEva (Geneva, Switzerland), Theramex (London, UK) and Kissei (Japan) and grant 5/4/150/5 was awarded to M.-M.D. by FNRS. J.D. was a member of the scientific advisory board of ObsEva until August 2022, a member of the scientific advisory board of PregLem, and received personal fees from Gedeon Richter, ObsEva and Theramex. J.D. received consulting fees, speakers' fees, and travel support from Gedeon Richter, Obseva and Theramex, which was paid to their institution. C.B. has received fees from Theramex, Gedeon Richter, and Myovant, and travel support from Gedeon Richter-all funds went to the University of Oxford. He was a member of the data monitoring board supervising the current study, and served at an advisory board for endometriosis studies of Myovant. H.T. has received grants from Abbvie and was past president of ASRM. F.C.H. has received fees from Gedeon Richter and Theramex. O.D. received fees for lectures from Gedeon Richter and ObsEva and research grants for clinical studies from Preglem and ObsEva independent from the current study. A.H. has received grants from NIHR, UKRI, CSO, Wellbeing of Women, and Roche Diagnostics; he has received fees from Theramex. A.H.'s institution has received honoraria for consultancy from Roche Diagnostics, Gesynta, and Joii. M.P. has nothing to declare. F.P. has received fees from Theramex. S.P.R. has been a member of the scientific advisory board of Gedeon Richter and received fees from Gedeon Richter. A.P. and M.B. are employees of Theramex. E.B. was an employee of ObsEva, sponsor chair of the data monitoring board supervising the current study, and has been working as a consultant for Theramex since December 2022; she owns stock options in ObsEva. M.-M.D. has received fees and travel support from Gedeon Richter and Theramex. TRIAL REGISTRATION NUMBER: NCT03992846. TRIAL REGISTRATION DATE: 20 June 2019. DATE OF FIRST PATIENT'S ENROLLMENT: 13 June 2019.

Factors Related to the Development of Infective Endocarditis in Hemodialysis Patients in a Third-Level Hospital in Panama.

INTRODUCTION: Venous access for hemodialysis (HD) makes patients more susceptible to transient bacteremia, predisposing them to the development of infective endocarditis (IE). Among the risk factors observed in this population are temporary access to HD, hypoalbuminemia, diabetes mellitus, female gender, anemia, and colonization by methicillin-resistant Staphylococcus aureus (MRSA). METHODOLOGY: A retrospective case-control study with a one-to-two ratio was carried out on patients with chronic kidney disease (CKD) undergoing renal replacement therapy with at least one vascular access for HD at Complejo Hospitalario Dr. Arnulfo Arias Madrid (CHDrAAM) from 2010 to 2020. Sociodemographic variables, past medical history, and data on current HD were studied. The odds ratio (OR) and adjusted odds ratio (aOR) were calculated for the collected variables. RESULTS: No statistically significant differences between the groups were observed in sociodemographic variables. In terms of past medical history, the cases showed a predominance of coronary disease (47.6% vs 4.8%; OR: 37.27), valvular disease (23.8% vs 0%), and heart failure (33.3% vs 4.8%; OR: 10). In the cases, the use of a temporary catheter was more prevalent (61.9% vs 33.3%; OR: 3.25), and subclavian access was more frequently recorded (28.6% vs 2.4%; OR: 14.4). A short duration of venous access (<30 days) was found in a greater proportion of cases (23.8% vs 4.8%; OR: 6.25). The main pathogen isolated was S. aureus (33.3%), and the most affected valve was the aortic valve (59.1%). Fever was found in 100% of the reported cases, and up to 47.6% presented with a recent murmur. DISCUSSION: Similar to previous studies conducted in other countries, we identified a history of pre-existing valve disease, the use of a temporary catheter, and recent venous access as risk factors. Contrary to what has been reported in the literature, this study did not find female sex, diabetes mellitus, and hypoalbuminemia as risks. CONCLUSION: Factors such as a history of coronary artery disease, heart failure, preexisting valvular disease, the use of a temporary catheter, subclavian venous access, and short duration of venous access (<30 days) were identified as risk factors for the development of IE in patients with CKD on HD.

Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation.

Airway segmentation is crucial for the examination, diagnosis, and prognosis of lung diseases, while its manual delineation is unduly burdensome. To alleviate this time-consuming and potentially subjective manual procedure, researchers have proposed methods to automatically segment airways from computerized tomography (CT) images. However, some small-sized airway branches (e.g., bronchus and terminal bronchioles) significantly aggravate the difficulty of automatic segmentation by machine learning models. In particular, the variance of voxel values and the severe data imbalance in airway branches make the computational module prone to discontinuous and false-negative predictions, especially for cohorts with different lung diseases. The attention mechanism has shown the capacity to segment complex structures, while fuzzy logic can reduce the uncertainty in feature representations. Therefore, the integration of deep attention networks and fuzzy theory, given by the fuzzy attention layer, should be an escalated solution for better generalization and robustness. This article presents an efficient method for airway segmentation, comprising a novel fuzzy attention neural network (FANN) and a comprehensive loss function to enhance the spatial continuity of airway segmentation. The deep fuzzy set is formulated by a set of voxels in the feature map and a learnable Gaussian membership function. Different from the existing attention mechanism, the proposed channel-specific fuzzy attention addresses the issue of heterogeneous features in different channels. Furthermore, a novel evaluation metric is proposed to assess both the continuity and completeness of airway structures. The efficiency, generalization, and robustness of the proposed method have been proved by training on normal lung disease while testing on datasets of lung cancer, COVID-19, and pulmonary fibrosis.

Handling Imbalanced Classification Problems With Support Vector Machines via Evolutionary Bilevel Optimization.

Support vector machines (SVMs) are popular learning algorithms to deal with binary classification problems. They traditionally assume equal misclassification costs for each class; however, real-world problems may have an uneven class distribution. This article introduces EBCS-SVM: evolutionary bilevel cost-sensitive SVMs. EBCS-SVM handles imbalanced classification problems by simultaneously learning the support vectors and optimizing the SVM hyperparameters, which comprise the kernel parameter and misclassification costs. The resulting optimization problem is a bilevel problem, where the lower level determines the support vectors and the upper level the hyperparameters. This optimization problem is solved using an evolutionary algorithm (EA) at the upper level and sequential minimal optimization (SMO) at the lower level. These two methods work in a nested fashion, that is, the optimal support vectors help guide the search of the hyperparameters, and the lower level is initialized based on previous successful solutions. The proposed method is assessed using 70 datasets of imbalanced classification and compared with several state-of-the-art methods. The experimental results, supported by a Bayesian test, provided evidence of the effectiveness of EBCS-SVM when working with highly imbalanced datasets.

A Trust Risk Dynamic Management Mechanism Based on Third-Party Monitoring for the Conflict-Eliminating Process of Social Network Group Decision Making.

Every decision may involve risks. Real-world risk issues are usually supervised by third parties. Decision-making may be affected by the absence of sufficient or reasonable trust or to the opposite, an unconditional, excessive, or blind trust, which is called trust risks. The conflict-eliminating process (CEP) aims to facilitate satisfactory consensus by decision makers (DMs) through continuous reconciliation between their opinion differences on the subject matter. This article addresses trust risks in CEP of social network group decision making (SNGDM) through third-party monitoring. A trust risk analysis-based conflict-eliminating model for SNGDM is developed. It is assumed that a third-party agency monitors the DMs' credibility and performance, which is recorded in an objective evaluation matrix and multi-attribute trust assessment matrix (MTAM). A trust risk measurement methodology is proposed to classify the DMs' different trust risk types and to measure the trust risk index (TRI) of a group of DMs. When TRI is unacceptable, a trust risk management mechanism that controls TRI is activated. Different management policies are applicable to DMs' different trust risk types. There are two main methods: 1) dynamically update the MTAM based on DMs' performance and 2) provide suggestions for modifying the DM's information with high TRI. Besides, as part of the integrated CEP, this model includes an optimization approach to dynamically derive DMs' reliable aggregation weights from their MTAM. Simulation experiments and an illustrative example support the feasibility and validity of the proposed model for managing trust risks in CEP of SNGDM.

EvoPruneDeepTL: An evolutionary pruning model for transfer learning based deep neural networks.

In recent years, Deep Learning models have shown a great performance in complex optimization problems. They generally require large training datasets, which is a limitation in most practical cases. Transfer learning allows importing the first layers of a pre-trained architecture and connecting them to fully-connected layers to adapt them to a new problem. Consequently, the configuration of the these layers becomes crucial for the performance of the model. Unfortunately, the optimization of these models is usually a computationally demanding task. One strategy to optimize Deep Learning models is the pruning scheme. Pruning methods are focused on reducing the complexity of the network, assuming an expected performance penalty of the model once pruned. However, the pruning could potentially be used to improve the performance, using an optimization algorithm to identify and eventually remove unnecessary connections among neurons. This work proposes EvoPruneDeepTL, an evolutionary pruning model for Transfer Learning based Deep Neural Networks which replaces the last fully-connected layers with sparse layers optimized by a genetic algorithm. Depending on its solution encoding strategy, our proposed model can either perform optimized pruning or feature selection over the densely connected part of the neural network. We carry out different experiments with several datasets to assess the benefits of our proposal. Results show the contribution of EvoPruneDeepTL and feature selection to the overall computational efficiency of the network as a result of the optimization process. In particular, the accuracy is improved, reducing at the same time the number of active neurons in the final layers.

Interaction Dynamics with Babies During Shared Reading Practices / Dinâmicas de Interação em Situações de Leitura Compartilhada com Bebês / Dinámicas de Interacción con Bebés durante Momentos de Lectura Compartida

Abstract This paper examines the triadic dynamics of baby-teacher-book during shared reading in an Early Childhood Education School to explain how educational teaching practices can enhance initial reading experiences and development processes in Early Childhood. A ten-months-old baby and a teacher participated in this study and, as an instrument for data collection, reading situations were registered and later these sessions were weighted through use of microgenetic analysis. From the analysis of the data present in the detailed case, it was identified the emergence of qualitative indicators that favoured the involvement of the baby in the activity, the mediation and educational actions of the teacher and the use of the book were more frequent. The effective use of the object book with that baby has contributed to qualitative changes in the baby's development and learning and emphasizes the incentive to share reading with other children.

Resumo Este estudo teve como objetivo examinar a dinâmica da tríade bebê-professora-livro durante a leitura compartilhada em uma Escola de Educação Infantil a fim de explicar como as práticas educativas de ensino potencializam experiências iniciais de leitura e processos de desenvolvimento na Primeira Infância. Uma bebê de dez meses e uma professora participaram desse estudo e como instrumento para coleta de dados foi utilizado a vídeogravação de momentos de leitura e posteriormente essas sessões foram ponderadas através da análise microgenética. A partir das análises dos dados presentes no caso detalhado, identificou-se a emergência de indicadores qualitativos que favoreceram o engajamento da bebê na atividade, sendo que a mediação e ações educativas da professora e do uso do livro foram mais frequentes. O uso efetivo do livro-objeto pode ter contribuído para mudanças qualitativas no desenvolvimento e aprendizagem da bebê e enfatiza a necessidade de incentivar o compartilhamento da leitura nessas idades.

Resumen Este artículo tuvo como objetivo examinar la dinámica de la tríada bebé-maestra-libro durante la lectura compartida en una Escuela de Educación Infantil con el fin de explicar cómo las prácticas docentes educativas pueden potenciar las experiencias iniciales de lectura y los procesos de desarrollo en la Primera Infancia. En este estudio participó una bebé de diez meses y una maestra y como instrumento de recolección de datos se utilizó la grabación en video de los momentos de lectura y posteriormente estas sesiones fueron ponderadas a través del análisis microgenético. A partir del análisis de los datos presentes en este caso, se identificó la emergencia de indicadores cualitativos que favorecen la participación de la bebé en la actividad, siendo más frecuentes la mediación y las acciones educativas de la docente, así como el uso del libro. El uso efectivo del libro objeto con la bebé ha contribuido a cambios cualitativos en el desarrollo y aprendizaje de los niños y enfatiza el incentivo de compartir la lectura con otros niños pequeños.

Sentinel2GlobalLULC: A Sentinel-2 RGB image tile dataset for global land use/cover mapping with deep learning.

Land-Use and Land-Cover (LULC) mapping is relevant for many applications, from Earth system and climate modelling to territorial and urban planning. Global LULC products are continuously developing as remote sensing data and methods grow. However, there still exists low consistency among LULC products due to low accuracy in some regions and LULC types. Here, we introduce Sentinel2GlobalLULC, a Sentinel-2 RGB image dataset, built from the spatial-temporal consensus of up to 15 global LULC maps available in Google Earth Engine. Sentinel2GlobalLULC v2.1 contains 194877 single-class RGB image tiles organized into 29 LULC classes. Each image is a 224 × 224 pixels tile at 10 × 10 m resolution built as a cloud-free composite from Sentinel-2 images acquired between June 2015 and October 2020. Metadata includes a unique LULC annotation per image, together with level of consensus, reverse geo-referencing, global human modification index, and number of dates used in the composite. Sentinel2GlobalLULC is designed for training deep learning models aiming to build precise and robust global or regional LULC maps.

Discovery of MDV6058 (PF-06952229), a selective and potent TGFßR1 inhibitor: Design, synthesis and optimization.

Compound 1 is a potent TGF-ß receptor type-1 (TGFßR1 or ALK5) inhibitor but is metabolically unstable. A solvent-exposed part of this molecule was used to analogue and modulate cell activity, liver microsome stability and mouse pharmacokinetics. The evolution of SAR that led to the selection of 2 (MDV6058 / PF-06952229) as a preclinical lead compound is described.

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions.

Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research.

Prevalence of bleeding secondary to anticoagulation and mortality in patients with atrial fibrillation admitted with SARS-CoV-2 infection.

Introduction and purpose: Atrial fibrillation (AF) is common in patients admitted with severe COVID-19. However, there is limited data about the management of chronic anticoagulation therapy in these patients. We assessed the anticoagulation and incidence of major cardiovascular events in hospitalized patients with AF and COVID-19. Methods: We retrospectively investigated all consecutive patients with AF admitted with COVID-19 between March and May 2020 in 9 Spanish hospitals. We selected a control group of non-AF patients consecutively admitted with COVID-19. We compared baseline characteristics, incidence of major bleeding, thrombotic events and mortality. We used propensity score matching (PSM) to minimize potential confounding variables, as well as a multivariate analysis to predict major bleeding and death. Results: 305 patients admitted with AF and COVID-19 were included. After PSM, 151 AF patients were matched with 151 control group patients. During admission, low-molecular-weight heparin was the principal anticoagulant and the incidence of major bleeding and mortality were higher in the AF group [16 (10.6%) vs 3 (2%), p = 0.003; 52 (34.4%) vs 35 (23.2%), p = 0.03, respectively]. The multivariate analysis showed the presence of AF as independent predictor of in-hospital major bleeding and mortality in COVID-19 patients. In AF group, a secondary multivariate analysis identified high levels of D-dimer as independent predictor of in-hospital major bleeding. Conclusions: AF patients admitted with COVID-19 represent a population at high risk for bleeding and mortality during admission. It seems advisable to individualize anticoagulation therapy during admission, considering patient specific bleeding and thrombotic risk.

Antecedentes y objetivos: La fibrilación auricular (FA) es frecuente en pacientes ingresados por COVID-19 grave. Sin embargo, los datos sobre el manejo de la anticoagulación crónica en estos pacientes son escasos. Analizamos la anticoagulación y la incidencia de episodios cardiovasculares mayores en pacientes con FA ingresados por la COVID-19. Métodos: Retrospectivamente, se identificaron todos los pacientes con FA ingresados por la COVID-19 entre marzo y mayo de 2020, en 9 hospitales españoles. Se seleccionó un grupo control de pacientes ingresados consecutivamente por la COVID-19 sin FA. Se compararon las características basales, incidencia de hemorragias mayores, episodios trombóticos y mortalidad. Para reducir potenciales factores de confusión se realizó un emparejamiento por puntuación de propensión, así como un análisis multivariante para predecir hemorragia mayor y mortalidad. Resultados: Se incluyeron 305 pacientes con FA ingresados por la COVID-19. Tras el emparejamiento por puntuación de propensión, 151 pacientes con FA fueron emparejados con 151 controles. Durante el ingreso, la heparina de bajo peso molecular fue el principal anticoagulante y la incidencia de hemorragia mayor y mortalidad fue mayor en el grupo de FA (16[10,6%] vs. 3[2%], p = 0,003; 52[34,4%] vs. 35[23,2%], p = 0,03, respectivamente). El análisis multivariante demostró la presencia de FA como predictor independiente de sangrados y mortalidad intrahospitalaria en los pacientes con la COVID-19. En el grupo de FA, un segundo análisis multivariante identificó valores elevados de dímero-D como predictor independiente de hemorragia mayor intrahospitalaria. Conclusiones: Los pacientes con FA ingresados por la COVID-19 representan una población de alto riesgo de sangrado y mortalidad durante el ingreso. Parece recomendable individualizar la anticoagulación durante el ingreso, considerando el riesgo específico de sangrado y trombosis.

Prevalence of bleeding secondary to anticoagulation and mortality in patients with atrial fibrillation admitted with SARS-CoV-2 infection / Prevalencia de hemorragia secundaria a anticoagulación y mortalidad en pacientes con fibrilación auricular ingresados por infección por SARS-CoV-2

Introduction and purpose:Atrial fibrillation (AF) is common in patients admitted with severe COVID-19. However, there is limited data about the management of chronic anticoagulation therapy in these patients. We assessed the anticoagulation and incidence of major cardiovascular events in hospitalized patients with AF and COVID-19.Methods:We retrospectively investigated all consecutive patients with AF admitted with COVID-19 between March and May 2020 in 9 Spanish hospitals. We selected a control group of non-AF patients consecutively admitted with COVID-19. We compared baseline characteristics, incidence of major bleeding, thrombotic events and mortality. We used propensity score matching (PSM) to minimize potential confounding variables, as well as a multivariate analysis to predict major bleeding and death.Results:305 patients admitted with AF and COVID-19 were included. After PSM, 151 AF patients were matched with 151 control group patients. During admission, low-molecular-weight heparin was the principal anticoagulant and the incidence of major bleeding and mortality were higher in the AF group [16 (10.6%) vs 3 (2%), p=0.003; 52 (34.4%) vs 35 (23.2%), p=0.03, respectively]. The multivariate analysis showed the presence of AF as independent predictor of in-hospital major bleeding and mortality in COVID-19 patients. In AF group, a secondary multivariate analysis identified high levels of D-dimer as independent predictor of in-hospital major bleeding.Conclusions:AF patients admitted with COVID-19 represent a population at high risk for bleeding and mortality during admission. It seems advisable to individualize anticoagulation therapy during admission, considering patient specific bleeding and thrombotic risk. (AU)

Antecedentes y objetivos:La fibrilación auricular (FA) es frecuente en pacientes ingresados por COVID-19 grave. Sin embargo, los datos sobre el manejo de la anticoagulación crónica en estos pacientes son escasos. Analizamos la anticoagulación y la incidencia de episodios cardiovasculares mayores en pacientes con FA ingresados por la COVID-19.Métodos:Retrospectivamente, se identificaron todos los pacientes con FA ingresados por la COVID-19 entre marzo y mayo de 2020, en 9 hospitales españoles. Se seleccionó un grupo control de pacientes ingresados consecutivamente por la COVID-19 sin FA. Se compararon las características basales, incidencia de hemorragias mayores, episodios trombóticos y mortalidad. Para reducir potenciales factores de confusión se realizó un emparejamiento por puntuación de propensión, así como un análisis multivariante para predecir hemorragia mayor y mortalidad.Resultados:Se incluyeron 305 pacientes con FA ingresados por la COVID-19. Tras el emparejamiento por puntuación de propensión, 151 pacientes con FA fueron emparejados con 151 controles. Durante el ingreso, la heparina de bajo peso molecular fue el principal anticoagulante y la incidencia de hemorragia mayor y mortalidad fue mayor en el grupo de FA (16[10,6%] vs. 3[2%], p=0,003; 52[34,4%] vs. 35[23,2%], p=0,03, respectivamente). El análisis multivariante demostró la presencia de FA como predictor independiente de sangrados y mortalidad intrahospitalaria en los pacientes con la COVID-19. En el grupo de FA, un segundo análisis multivariante identificó valores elevados de dímero-D como predictor independiente de hemorragia mayor intrahospitalaria.Conclusiones:Los pacientes con FA ingresados por la COVID-19 representan una población de alto riesgo de sangrado y mortalidad durante el ingreso. Parece recomendable individualizar la anticoagulación durante el ingreso, considerando el riesgo específico de sangrado y trombosis. (AU)

Replacing pooling functions in Convolutional Neural Networks by linear combinations of increasing functions.

Traditionally, Convolutional Neural Networks make use of the maximum or arithmetic mean in order to reduce the features extracted by convolutional layers in a downsampling process known as pooling. However, there is no strong argument to settle upon one of the two functions and, in practice, this selection turns to be problem dependent. Further, both of these options ignore possible dependencies among the data. We believe that a combination of both of these functions, as well as of additional ones which may retain different information, can benefit the feature extraction process. In this work, we replace traditional pooling by several alternative functions. In particular, we consider linear combinations of order statistics and generalizations of the Sugeno integral, extending the latter's domain to the whole real line and setting the theoretical base for their application. We present an alternative pooling layer based on this strategy which we name "CombPool" layer. We replace the pooling layers of three different architectures of increasing complexity by CombPool layers, and empirically prove over multiple datasets that linear combinations outperform traditional pooling functions in most cases. Further, combinations with either the Sugeno integral or one of its generalizations usually yield the best results, proving a strong candidate to apply in most architectures.

Female sexuality before and after sacrocolpopexy or vaginal mesh: is vaginal length one of the key factors?

INTRODUCTION AND HYPOTHESIS: We aimed to demonstrate that laparoscopic sacrocolpopexy/cervicopexy (LSC-Cx) versus anterior vaginal mesh (AVM) results in a longer vaginal length without impacting sexual activity or function. METHODS: We performed a secondary analysis of sexual outcomes of a previous randomized control trial comparing LSC-Cx and AVM in 120 women (60/group) with symptomatic POP stage ≥ 3. We evaluated sexually active (SA) and non-sexually active women (NSA) using the Pelvic Organ Prolapse/Incontinence Sexual Questionnaire-IUGA-Revised (PISQ-IR) preoperatively and 1 year postoperatively. Multivariate logistic and linear regression models were built to assess the impact of different variables on sexual activity and function, respectively. RESULTS: Among 120 women included, no statistically significant differences were found between vaginal length and preoperative dyspareunia (20.7% AVM vs. 22,8% LSC-Cx) comparing SA to NSA women and LSC-Cx to AVM. Vaginal length was significantly longer after LSC-Cx versus AVM (p < 0.001). The postoperative dyspareunia rate was 17.2% AVM versus 10.5% LSC-Cx. Partnered women were significantly more likely to be SA than unpartnered women before (OR = 19.04; p = 0.006) and after surgery (OR = 36.28; p = 0.002). Only dyspareunia was independently associated with sexual function pre- (B = -0.431; p = 0.017) and postoperatively (B = -0.3 96; p = 0.007). CONCLUSIONS: Vaginal length was greater following LSC-Cx compared to AVM. While vaginal length has no impact on female sexuality pre- and postoperatively, the most important factors were "having a partner" for sexual activity and dyspareunia for sexual function. Persistence of dyspareunia was higher after AVM. LSC-Cx should be considered in women with POP undergoing mesh surgery with future sexual expectations.

Prevalence of bleeding secondary to anticoagulation and mortality in patients with atrial fibrillation admitted with SARS-CoV-2 infection.

INTRODUCTION AND PURPOSE: Atrial fibrillation (AF) is common in patients admitted with severe COVID-19. However, there is limited data about the management of chronic anticoagulation therapy in these patients. We assessed the anticoagulation and incidence of major cardiovascular events in hospitalized patients with AF and COVID-19. METHODS: We retrospectively investigated all consecutive patients with AF admitted with COVID-19 between March and May 2020 in 9 Spanish hospitals. We selected a control group of non-AF patients consecutively admitted with COVID-19. We compared baseline characteristics, incidence of major bleeding, thrombotic events and mortality. We used propensity score matching (PSM) to minimize potential confounding variables, as well as a multivariate analysis to predict major bleeding and death. RESULTS: 305 patients admitted with AF and COVID-19 were included. After PSM, 151 AF patients were matched with 151 control group patients. During admission, low-molecular-weight heparin was the principal anticoagulant and the incidence of major bleeding and mortality were higher in the AF group [16 (10.6%) vs 3 (2%), p=0.003; 52 (34.4%) vs 35 (23.2%), p=0.03, respectively]. The multivariate analysis showed the presence of AF as independent predictor of in-hospital major bleeding and mortality in COVID-19 patients. In AF group, a secondary multivariate analysis identified high levels of D-dimer as independent predictor of in-hospital major bleeding. CONCLUSIONS: AF patients admitted with COVID-19 represent a population at high risk for bleeding and mortality during admission. It seems advisable to individualize anticoagulation therapy during admission, considering patient specific bleeding and thrombotic risk.

Reducing Data Complexity Using Autoencoders With Class-Informed Loss Functions.

Available data in machine learning applications is becoming increasingly complex, due to higher dimensionality and difficult classes. There exists a wide variety of approaches to measuring complexity of labeled data, according to class overlap, separability or boundary shapes, as well as group morphology. Many techniques can transform the data in order to find better features, but few focus on specifically reducing data complexity. Most data transformation methods mainly treat the dimensionality aspect, leaving aside the available information within class labels which can be useful when classes are somehow complex. This paper proposes an autoencoder-based approach to complexity reduction, using class labels in order to inform the loss function about the adequacy of the generated variables. This leads to three different new feature learners, Scorer, Skaler and Slicer. They are based on Fisher's discriminant ratio, the Kullback-Leibler divergence and least-squares support vector machines, respectively. They can be applied as a preprocessing stage for a binary classification problem. A thorough experimentation across a collection of 27 datasets and a range of complexity and classification metrics shows that class-informed autoencoders perform better than 4 other popular unsupervised feature extraction techniques, especially when the final objective is using the data for a classification task.

A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects.

The17 Sustainable Development Goals (SDGs) established by the United Nations Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity worldwide. Artificial intelligence and other digital technologies that have emerged in the last years, are being currently applied in virtually every area of society, economy and the environment. Hence, it is unsurprising that their current role in the pursuance or hampering of the SDGs has become critical. This study aims at providing a snapshot and comprehensive view of the progress made and prospects in the relationship between artificial intelligence technologies and the SDGs. A comprehensive review of existing literature has been firstly conducted, after which a series SWOT (Strengths, Weaknesses, Opportunities and Threats) analyses have been undertaken to identify the strengths, weaknesses, opportunities and threats inherent to artificial intelligence-driven technologies as facilitators or barriers to each of the SDGs. Based on the results of these analyses, a subsequent broader analysis is provided, from a position vantage, to (i) identify the efforts made in applying AI technologies in SDGs, (ii) pinpoint opportunities for further progress along the current decade, and (iii) distill ongoing challenges and target areas for important advances. The analysis is organized into six categories or perspectives of human needs: life, economic and technological development, social development, equality, resources and natural environment. Finally, a closing discussion is provided about the prospects, key guidelines and lessons learnt that should be adopted for guaranteeing a positive shift of artificial intelligence developments and applications towards fully supporting the SDGs attainment by 2030.

Características clínicas asociadas al hallazgo de cáncer de tiroides originado a partir de nódulos calientes en pacientes con hipertiroidismo: reporte de un caso y revisión sistemática de la literatura / Clinical characteristics associated with the finding of thyroid cancer originating from hot nodules in patients with hyperthyroidism: a case report and systematic review of the literature

Abstract Coexistence between thyroid cancer and hyperthyroidism is rare, and most of the nodular lesions from which a malignant tumor is documented in this group of patients correspond to cold nodules. Justified by the increasing number of reports in the literature about malignant tumors diagnosed from hot nodules, a systematic review was carried out to determine possible factors associated with the diagnosis of thyroid cancer from hot nodules in patients with hyperthyroidism. The results suggest that the clinical diagnosis of toxic nodular goiter, nodular lesions of diameter > 10 mm and a histological type compatible with a follicular carcinoma, are factors that on their own increase the risk of making the diagnosis of cancer from a hot nodule.

Resumen La coexistencia entre cáncer de tiroides e hipertiroidismo es infrecuente, y la mayoría de las lesiones nodulares a partir de las cuales se documenta un tumor maligno en este grupo de pacientes corresponden a nódulos fríos. Justificado en el creciente número de reportes en la literatura acerca de tumores malignos diagnosticados a partir de nódulos calientes, se realizó una revisión sistemática que tuvo como objetivo determinar los posibles factores asociados con el diagnóstico de cáncer de tiroides a partir de nódulos calientes en pacientes con hipertiroidismo. Los resultados sugieren que el diagnóstico clínico de bocio nodular tóxico, lesiones nodulares de diámetro mayor de 10 mm y tipo histológico compatible con carcinoma folicular, son factores que aumentan por sí solos el riesgo de realizar el diagnóstico de cáncer a partir de un nódulo caliente.

Características clínicas asociadas al hallazgo de cáncer de tiroides originado a partir de nódulos calientes en pacientes con hipertiroidismo: reporte de un caso y revisión sistemática de la literatura / Clinical characteristics associated with the finding of thyroid cancer originating from hot nodules in patients with hyperthyroidism: a case report and systematic review of the literature

La coexistencia entre cáncer de tiroides e hipertiroidismo es infrecuente, y la mayoría de las lesiones nodulares a partir de las cuales se documenta un tumor maligno en este grupo de pacientes corresponden a nódulos fríos. Justificado en el creciente número de reportes en la literatura acerca de tumores malignos diagnosticados a partir de nódulos calientes, se realizó una revisión sistemática que tuvo como objetivo determinar los posibles factores asociados con el diagnóstico de cáncer de tiroides a partir de nódulos calientes en pacientes con hipertiroidismo. Los resultados sugieren que el diagnóstico clínico de bocio nodular tóxico, lesiones nodulares de diámetro mayor de 10 mm y tipo histológico compatible con carcinoma folicular, son factores que aumentan por sí solos el riesgo de realizar el diagnóstico de cáncer a partir de un nódulo caliente

Coexistence between thyroid cancer and hyperthyroidism is rare, and most of the nodular lesions from which a malignant tumor is documented in this group of patients correspond to cold nodules. Justified by the increasing number of reports in the literature about malignant tumors diagnosed from hot nodules, a systematic review was carried out to determine possible factors associated with the diagnosis of thyroid cancer from hot nodules in pa-tients with hyperthyroidism. The results suggest that the clinical diagnosis of toxic nodular goiter, nodular lesions of diameter > 10 mm and a histological type compatible with a follicular carcinoma, are factors that on their own increase the risk of making the diagnosis of cancer from a hot nodule

Un pequeño paso para el cirujano, un gran salto para la cirugía / A small step for the surgeon, a big jump for the surgery

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