RSAFormer: A method of polyp segmentation with region self-attention transformer.

Colonoscopy has attached great importance to early screening and clinical diagnosis of colon cancer. It remains a challenging task to achieve fine segmentation of polyps. However, existing State-of-the-art models still have limited segmentation ability due to the lack of clear and highly similar boundaries between normal tissue and polyps. To deal with this problem, we propose a region self-attention enhancement network (RSAFormer) with a transformer encoder to capture more robust features. Different from other excellent methods, RSAFormer uniquely employs a dual decoder structure to generate various feature maps. Contrasting with traditional methods that typically employ a single decoder, it offers more flexibility and detail in feature extraction. RSAFormer also introduces a region self-attention enhancement module (RSA) to acquire more accurate feature information and foster a stronger interplay between low-level and high-level features. This module enhances uncertain areas to extract more precise boundary information, these areas being signified by regional context. Extensive experiments were conducted on five prevalent polyp datasets to demonstrate RSAFormer's proficiency. It achieves 92.2% and 83.5% mean Dice on Kvasir and ETIS, respectively, which outperformed most of the state-of-the-art models.

Long-Term Outcomes of Pharmacoinvasive Strategy Versus Primary Percutaneous Coronary Intervention in ST-Elevation Myocardial Infarction: A Study from Mexico City.

Although primary percutaneous coronary intervention (pPCI) is the treatment of choice in ST-elevation myocardial infarction (STEMI), challenges may arise in accessing this intervention for certain geodemographic groups. Pharmacoinvasive strategy (PIs) has demonstrated comparable outcomes when delays in pPCI are anticipated, but real-world data on long-term outcomes are limited. The aim of the present study was to compare long-term outcomes among real-world patients with STEMI who underwent either PIs or pPCI. This was a prospective registry including patients with STEMI who received reperfusion during the first 12 hours from symptom onset. The primary objective was cardiovascular mortality at 12 months according to the reperfusion strategy (pPCI vs PIs) and major cardiovascular events (cardiogenic shock, recurrent myocardial infarction, and congestive heart failure), and Bleeding Academic Research Consortium type 3 to 5 bleeding events were also evaluated. A total of 799 patients with STEMI were included; 49.1% underwent pPCI and 50.9% received PIs. Patients in the PIs group presented with more heart failure on admission (Killip-Kimbal >I 48.1 vs 39.7, p = 0.02) and had a lower proportion of pre-existing heart failure (0.2% vs 1.8%, p = 0.02) and atrial fibrillation (0.25% vs 1.2%, p = 0.02). No statistically significant difference was observed in cardiovascular mortality at the 12-month follow-up (hazard ratio for PIs 0.74, 95% confidence interval 0.42 to 1.30, log-rank p = 0.30) according to the reperfusion strategy used. The composite of major cardiovascular events (hazard ratio for PIs 0.98, 95% confidence interval 0.75 to 1.29, p = 0.92) and Bleeding Academic Research Consortium type 3 to 5 bleeding rates were also comparable. A low socioeconomic status, Killip-Kimball >2, age >60 years, and admission creatinine >2.0 mg/100 ml were predictors of the composite end point after multivariate analysis. In conclusion, this prospective real-world registry provides additional support that long-term major cardiovascular outcomes and bleeding are not different between patients who underwent PIs versus primary PCI.

Hybrid Gromov-Wasserstein Embedding for Capsule Learning.

Capsule networks (CapsNets) aim to parse images into a hierarchy of objects, parts, and their relationships using a two-step process involving part-whole transformation and hierarchical component routing. However, this hierarchical relationship modeling is computationally expensive, which has limited the wider use of CapsNet despite its potential advantages. The current state of CapsNet models primarily focuses on comparing their performance with capsule baselines, falling short of achieving the same level of proficiency as deep convolutional neural network (CNN) variants in intricate tasks. To address this limitation, we present an efficient approach for learning capsules that surpasses canonical baseline models and even demonstrates superior performance compared with high-performing convolution models. Our contribution can be outlined in two aspects: first, we introduce a group of subcapsules onto which an input vector is projected. Subsequently, we present the hybrid Gromov-Wasserstein (HGW) framework, which initially quantifies the dissimilarity between the input and the components modeled by the subcapsules, followed by determining their alignment degree through optimal transport (OT). This innovative mechanism capitalizes on new insights into defining alignment between the input and subcapsules, based on the similarity of their respective component distributions. This approach enhances CapsNets' capacity to learn from intricate, high-dimensional data while retaining their interpretability and hierarchical structure. Our proposed model offers two distinct advantages: 1) its lightweight nature facilitates the application of capsules to more intricate vision tasks, including object detection; and 2) it outperforms baseline approaches in these demanding tasks. Our empirical findings illustrate that HGW capsules (HGWCapsules) exhibit enhanced robustness against affine transformations, scale effectively to larger datasets, and surpass CNN and CapsNet models across various vision tasks.

Real-World Evaluation of a Pharmacoinvasive Strategy for STEMI in Latin America: A Cost-Effective Approach with Short-Term Benefits.

Purpose: While pharmacoinvasive strategy (PI) is a safe and effective approach whenever access to primary percutaneous intervention (pPCI) is limited, data on each strategy's economic cost and impact on in-hospital stay are scarce. The objective is to compare the cost-effectiveness of a PI with that of pPCI for the treatment of ST-elevation myocardial infarction (STEMI) in a Latin-American country. Patients and Methods: A total of 1747 patients were included, of whom 470 (26.9%) received PI, 433 (24.7%) pPCI, and 844 (48.3%) NR. The study's primary outcome was the incremental cost-effectiveness ratio (ICER) for PI compared with those for pPCI and non-reperfused (NR), calculated for 30-day major cardiovascular events (MACE), 30-day mortality, and length of stay. Results: For PI, the ICER estimates for MACE showed a decrease of $-35.81/per 1% (95 confidence interval, -114.73 to 64.81) compared with pPCI and a decrease of $-271.60/per 1% (95% CI, -1086.10 to -144.93) compared with NR. Also, in mortality, PI had an ICER decrease of $-129.50 (95% CI, -810.57, 455.06) compared to pPCI and $-165.27 (-224.06, -123.52) with NR. Finally, length of stay had an ICER reduction of -765.99 (-4020.68, 3141.65) and -283.40 (-304.95, -252.76) compared to pPCI and NR, respectively. Conclusion: The findings of this study suggest that PI may be a more efficient treatment approach for STEMI in regions where access to pPCI is limited or where patient and system delays are expected.

Analysis of immortal-time effect in post-infarction ventricular septal defect.

Introduction: Time-fixed analyses have traditionally been utilized to examine outcomes in post-infarction ventricular septal defect (VSD). The aims of this study were to: (1) analyze the relationship between VSD closure/non-closure and mortality; (2) assess the presence of immortal-time bias. Material and methods: In this retrospective cohort study, patients with ST-elevation myocardial infarction (STEMI) complicated by VSD. Time-fixed and time-dependent Cox regression methodologies were employed. Results: The study included 80 patients: surgical closure (n = 26), transcatheter closure (n = 20), or conservative management alone (n = 34). At presentation, patients without VSD closure exhibited high-risk clinical characteristics, had the shortest median time intervals from STEMI onset to VSD development (4.0, 4.0, and 2.0 days, respectively; P = 0.03) and from STEMI symptom onset to hospital arrival (6.0, 5.0, and 0.8 days, respectively; P < 0.0001). The median time from STEMI onset to closure was 22.0 days (P = 0.14). In-hospital mortality rate was higher among patients who did not undergo defect closure (50%, 35%, and 88.2%, respectively; P < 0.0001). Closure of the defect using a fixed-time method was associated with lower in-hospital mortality (HR = 0.13, 95% CI 0.05-0.31, P < 0.0001, and HR 0.13, 95% CI 0.04-0.36, P < 0.0001, for surgery and transcatheter closure, respectively). However, when employing a time-varying method, this association was not observed (HR = 0.95, 95% CI 0.45-1.98, P = 0.90, and HR 0.88, 95% CI 0.41-1.87, P = 0.74, for surgery and transcatheter closure, respectively). These findings suggest the presence of an immortal-time bias. Conclusions: This study highlights that using a fixed-time analytic approach in post-infarction VSD can result in immortal-time bias. Researchers should consider employing time-dependent methodologies.

[Acute myocardial infarction patients without COVID-19 manifestations in the pandemic may have high thrombus burden]. / Pacientes con infarto agudo de miocardio sin manifestaciones de COVID-19 pueden tener alta carga de trombo.

Objective: The objective of the study is to identify clinical and angiographic characteristics of patients with ST-segment elevation myocardial infarction (STEMI) but without clinical manifestations of COVID-19 infection during the pandemic, compared with patients 1 year before the pandemic. Methods: Observational study that included 138 consecutive patients hospitalized with STEMI who underwent primary percutaneous coronary intervention (PCI) without COVID-19 infection during the 2020 pandemic. A group of 175 STEMI patients treated with PCI in the year before the pandemic served as the control group. Results: During the periods analyzed, compared with the control group, patients admitted during the pandemic without clinical manifestations of COVID-19 did not have significant differences in demographic characteristics, comorbidities, or delayed time and location of the acute myocardial infarction. Furthermore, there were no differences between the two groups concerning levels of CK-MB and NT-proBNP, or in inflammation markers and left ventricular ejection fraction. In patients without COVID-19 during the pandemic compared with control, we found a higher intracoronary thrombus burden (thrombus grade 5; 78.3% vs. 62.9%, respectively. p = 0.002). Accordingly, the use of glycoprotein IIB/IIIa inhibitors (37.7% vs. 26.3%, p = 0.03) was higher in these patients. Conclusions: This study demonstrates an increased thrombus burden in STEMI patients without clinical manifestation of COVID-19 during the pandemic compared with the same time period in the previous year.

Objetivo: Identificar las características clínicas y angiográficas de los pacientes con infarto agudo de miocardio con elevación del segmento ST (IAMCEST) sin manifestaciones clínicas de COVID-19 durante la pandemia y compararlos con los pacientes en el año previo. Métodos: Estudio observacional que incluyó 138 pacientes consecutivos que fueron hospitalizados por IAMCEST y que fueron tratados con angioplastía primaria (ACTP) sin manifestaciones clínicas de COVID-19 durante la pandemia de 2020. Se seleccionó a un grupo control de 175 pacientes con IAMCEST tratados con ACTP en el año previo a la pandemia. Resultados: Los pacientes atendidos durante la pandemia no tuvieron diferencias significativas en cuanto a las características clínicas, demográficas, comorbilidades, tiempo de retraso y localización del infarto. Además, no hubo diferencias entre ambos grupos en los niveles de CK-MB, NT-proBNP, marcadores de inflamación ni en la fracción de eyección del ventrículo izquierdo. En los pacientes sin COVID-19 tratados durante la pandemia encontramos mayor carga trombótica intracoronaria (trombo grado 5; 78.3% vs. 62.9%, respectivamente. p = 0.002). De igual manera, el uso de inhibidores de la glucoproteina IIB/IIIa (37.7% vs. 26.3%, p = 0.03) fue mayor. Conclusiones: Este studio demostró un aumento en la carga trombótica en los pacientes con IAMCEST sin manifestaciones clínicas de COVID-19 durante la pandemia al compararlos con los pacientes tratados por la misma patología en el año previo.

EpilepsyNet: Novel automated detection of epilepsy using transformer model with EEG signals from 121 patient population.

BACKGROUND: Epilepsy is one of the most common neurological conditions globally, and the fourth most common in the United States. Recurrent non-provoked seizures characterize it and have huge impacts on the quality of life and financial impacts for affected individuals. A rapid and accurate diagnosis is essential in order to instigate and monitor optimal treatments. There is also a compelling need for the accurate interpretation of epilepsy due to the current scarcity in neurologist diagnosticians and a global inequity in access and outcomes. Furthermore, the existing clinical and traditional machine learning diagnostic methods exhibit limitations, warranting the need to create an automated system using deep learning model for epilepsy detection and monitoring using a huge database. METHOD: The EEG signals from 35 channels were used to train the deep learning-based transformer model named (EpilepsyNet). For each training iteration, 1-min-long data were randomly sampled from each participant. Thereafter, each 5-s epoch was mapped to a matrix using the Pearson Correlation Coefficient (PCC), such that the bottom part of the triangle was discarded and only the upper triangle of the matrix was vectorized as input data. PCC is a reliable method used to measure the statistical relationship between two variables. Based on the 5 s of data, single embedding was performed thereafter to generate a 1-dimensional array of signals. In the final stage, a positional encoding with learnable parameters was added to each correlation coefficient's embedding before being fed to the developed EpilepsyNet as input data to epilepsy EEG signals. The ten-fold cross-validation technique was used to generate the model. RESULTS: Our transformer-based model (EpilepsyNet) yielded high classification accuracy, sensitivity, specificity and positive predictive values of 85%, 82%, 87%, and 82%, respectively. CONCLUSION: The proposed method is both accurate and robust since ten-fold cross-validation was employed to evaluate the performance of the model. Compared to the deep models used in existing studies for epilepsy diagnosis, our proposed method is simple and less computationally intensive. This is the earliest study to have uniquely employed the positional encoding with learnable parameters to each correlation coefficient's embedding together with the deep transformer model, using a huge database of 121 participants for epilepsy detection. With the training and validation of the model using a larger dataset, the same study approach can be extended for the detection of other neurological conditions, with a transformative impact on neurological diagnostics worldwide.

Training Proposal in Palliative Care for Primary Care Nurses in a Health Area in Spain.

BACKGROUND: Primary Health Care nurses express deficits in their training in Palliative Care. The purpose of this study is to design a Palliative Care training plan and a bereavement care protocol for Primary Health Care nurses of the Dr. Peset Health Department according to their needs. METHODS: Assessment of theoretical and practical training needs and literature review for the design of the training plan. RESULTS: A training plan was elaborated that included a protocol of care for the bereaved. The plan was adjusted to the needs detected in Primary Health Care nurses of the Dr. Peset Health Department. Important training deficits were detected in clinical practice; Conclusions: Improving the care of people with palliative needs in Primary Health Care requires adequate training of the nurses who care for them so their knowledge is the basis of their interventions. This study was not registered.

Women with Acute Myocardial Infarction: Clinical Characteristics, Treatment, and In-Hospital Outcomes from a Latin American Country.

Background: Women are underrepresented in acute myocardial infarction (AMI) studies. Furthermore, there is scarce information regarding women with AMI in Latin America. Aims: To describe the presentation, clinical characteristics, risk factor burden, evidence-based care, and in-hospital outcome in a population of women with AMI admitted to a coronary care unit (CCU) in Mexico. Methods: Retrospective cohort study including patients with AMI admitted from January 2006 to December 2021 in a CCU. We identified patients with ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI). We described demographic characteristics, clinical variables, treatment, and in-hospital outcomes according to gender. Cox regression analysis was used to identify predictors of mortality. Results: Our study included 12,069 patients with AMI, of whom 7,599 had STEMI and 4,470 had NSTEMI. Women represented 19.6% of the population. Women had higher rates of hypertension, diabetes, stroke, and atrial fibrillation than men. For STEMI, women were less likely to receive reperfusion therapy (fibrinolysis; 23.7 vs. 28.5%, p < 0.001 and primary percutaneous coronary intervention (PCI); 31.2 vs. 35.1%, p = 0.001) and had more major adverse events than men: heart failure (4.2 vs. 2.5%, p = 0.002), pulmonary edema (3.4% vs. 1.7%, p < 0.001), major bleeding (2.1% vs. 1%, p = 0.002), stroke (1.3% vs. 0.6%, p = 0.008), and mortality (15.1% vs. 8.1%, p < 0.001). For NSTEMI, women were less likely to undergo coronary angiography or PCI and had more major bleeding and mortality. Multivariate Cox regression analysis revealed that females had an increase in mortality in STEMI and NSTEMI (HR 1.21, CI 1.01-1.47, p = 0.05 and HR 1.39, CI 1.06-1.81, p = 0.01). Conclusion: Real-world evidence from a hospital in a Latin American low- to middle-income country (LMIC) showed that women with AMI had more comorbidities, received less reperfusion treatment or invasive strategies, and had worse outcomes. In STEMI and NSTEMI, female gender represented an independent predictor of in-hospital mortality.

Sex, Age, and Comorbidities Are Associated with SARS-CoV-2 Infection, COVID-19 Severity, and Fatal Outcome in a Mexican Population: A Retrospective Multi-Hospital Study.

People with comorbidities and the male sex are at a higher risk of developing severe COVID-19. In the present study, we aim to investigate the associated factors for infection, severity, and death due to COVID-19 in a population from Nuevo León, México. Epidemiological COVID-19 data were collected from 65 hospitals from December 2020 to May 2022. A total of 75,232 cases were compiled from which 25,722 cases were positive for SARS-CoV-2. Male sex, older age, diabetes, obesity, and hypertension were associated with infection. In addition to the above-mentioned factors, renal disease, cardiovascular disease, and immunosuppression were found to be associated with increased COVID-19 severity. These factors, as well as neurological diseases, are also associated with death due to COVID-19. When comparing the different variants of SARs-CoV-2, the variant B1.1.519 increased the probability of death by 2.23 times compared to the AY.20 variant. Male sex, older age, diabetes, obesity, and hypertension are associated with SARS-CoV-2 infection, severity, and death. Along with the aforementioned comorbidities, renal disease, cardiovascular disease, and immunosuppression are also associated with severity and death. Another factor associated with death is the presence of neurological disease. The SARS-CoV-2 B1.1.519 variant increases the odds of death compared to the SARS-CoV-2 AY.20 variant.

"Geographical distribution of risk genotypes in pediatric patients with celiac disease in Spain".

Celiac disease is strongly associated with HLA DQ, specifically with haplotypes. DRB1*03-DQA1*05:01/DQB1*02:01 (DQ2.5),DRB1*07-DQA1*02:01/DQB1*02:02 (DQ2.2), DRB1*11-DQA1*05:05/DQB1*03:01 (DQ7.5), and DRB1*04-DQA1*03:01/DQB1*03:02 (DQ8). The distribution of these risk haplotypes in patients with celiac disease is different in the geographical areas investigated. A high frequency of DRB1*07- DQA1*02:01/DQB1*02:02 (DQ2.2) and DRB1*11-DQA1*05:05/DQB1*03:01 (DQ7.5), has been described in Southern Europe. We analyzed 2102 confirmed CD cases with information on both DQB1* alelles and their distribution by geographical area in Spain. According to the presence of this haplotype in one or two chromosomes, the genotype is classified in: DQ2 homozygous, DQ2 heterozygous (cis or trans), DQ8 homozygous, DQ8/DQ2.5, DQ 2.2 homozygous and genotype known as "half DQ2". Two different patterns of risks related to CD were identified. In the Basque Country and Navarre, the Mediterranean Area (Aragon, Catalonia, Valencia, Balearic Islands, and Murcia), the South of Spain (Andalucía and Extremadura), and the Canary Islands, higher frequency of DQ2.5 trans, and more than 80% of DQ2.5/DQ2.2 homozygosis were described. The Cantabrian Coast (Cantabria, Asturias, and Galicia) and Central Areas (Castilla-León and Castilla-La Mancha) showed a higher percentage of DQ2.5/DQ2.5 homozygosis and a lower DQ2.5 in trans frequency, as in Northern Europe. Madrid has an intermediate model between the two described above. 17 cases (0.8%) did not carry any CD risk haplotypes.

Non-reperfused ST-elevation myocardial infarction: notions from a low-to-middle-income country / Infarto de miocardio con elevación del ST no reperfundido: nociones de un país de ingresos bajos a medios

Abstract Objective: The objective of the study was to analyze the differences between survivors and non-survivors with non-reperfused ST-segment elevation myocardial infarction (STEMI) and to identify the predictors of in-hospital mortality. Methods: A retrospective cohort study included non-reperfused STEMI patients from October 2005 to August 2020. Patients were classified into survivors and non-survivors. We compared patient characteristics, treatments, and outcomes among the groups and identified factors associated with in-hospital mortality. Results: We included 2442 patients with non-reperfused STEMI and we found a mortality of 12.7% versus 7.2% in reperfused STEMI. The main reason for non-reperfusion was delayed presentation (96.1%). Non-survivors were older, more often women, and had diabetes, hypertension, or atrial fibrillation. The left main coronary disease was more frequent in non-survivors as well as three-vessel disease. Non-survivors developed more in-hospital heart failure, reinfarction, atrioventricular block, bleeding, stroke, and death. The main predictors for in-hospital mortality were renal dysfunction (HR 3.41), systolic blood pressure < 100 mmHg (HR 2.26), and left ventricle ejection fraction < 40% (HR 1.97). Conclusion: Mortality and adverse outcomes occur more frequently in non-reperfused STEMI. Non-survivors tend to be older, with more comorbidities, and have more adverse in-hospital outcomes.

Resumen Objetivo: Analizar las diferencias entre los sobrevivientes y no sobrevivientes con infarto agudo de miocardio no reperfundido y conocer los predictores de mortalidad intrahospitalaria. Métodos: Estudio de cohorte retrospectiva que incluyó pacientes con infarto agudo de miocardio no reperfundido de octubre de 2005 a agosto de 2020. Se clasificaron los pacientes de acuerdo a su estado de sobrevida y se compararon las características clínicas, tratamientos y desenlaces para poder identificar los predictores de mortalidad intrahospitalaria. Resultados: Se incluyeron 2442 pacientes con infarto agudo de miocardio no reperfundido, en los que se encontró una mortalidad de 12.7% vs 7.2% los que si recibieron tratamiento de reperfusión. La principal razón para no recibir tratamiento de reperfusión fue el retraso en la atención médica (96.1%). Los no sobrevivientes tuvieron mayor edad, fueron mujeres y tuvieron mayor frecuencia de diabetes, hipertensión y fibrilación atrial. El tronco de la coronaria izquierda y la enfermedad trivascular fueron más frecuentes en los que no sobrevivieron. Los pacientes que no sobrevivieron desarrollaron más insuficiencia cardiaca, reinfarto, bloqueo atrioventricular, sangrados, evento vascular cerebral y muerte. Los principales predictores de mortalidad intrahospitalaria fueron: insuficiencia renal (HR 3.41), tensión arterial sistólica al ingreso < 100 mmHg (HR 2.26) y fracción de eyección del ventrículo izquierdo < 40% (HR 1.97). Conclusiones: Los pacientes con infarto de miocardio no reperfundido tienen mayor mortalidad y desenlaces adversos. Los no sobrevivientes fueron mayores, con más comorbilidades y desarrollaron más desenlaces adversos intrahospitalarios.

Non-reperfused ST-elevation myocardial infarction: notions from a low-to-middle-income country.

OBJECTIVE: The objective of the study was to analyze the differences between survivors and non-survivors with non-reperfused ST-segment elevation myocardial infarction (STEMI) and to identify the predictors of in-hospital mortality. METHODS: A retrospective cohort study included non-reperfused STEMI patients from October 2005 to August 2020. Patients were classified into survivors and non-survivors. We compared patient characteristics, treatments, and outcomes among the groups and identified factors associated with in-hospital mortality. RESULTS: We included 2442 patients with non-reperfused STEMI and we found a mortality of 12.7% versus 7.2% in reperfused STEMI. The main reason for non-reperfusion was delayed presentation (96.1%). Non-survivors were older, more often women, and had diabetes, hypertension, or atrial fibrillation. The left main coronary disease was more frequent in non-survivors as well as three-vessel disease. Non-survivors developed more in-hospital heart failure, reinfarction, atrioventricular block, bleeding, stroke, and death. The main predictors for in-hospital mortality were renal dysfunction (HR 3.41), systolic blood pressure < 100 mmHg (HR 2.26), and left ventricle ejection fraction < 40% (HR 1.97). CONCLUSION: Mortality and adverse outcomes occur more frequently in non-reperfused STEMI. Non-survivors tend to be older, with more comorbidities, and have more adverse in-hospital outcomes.

OBJETIVO: Analizar las diferencias entre los sobrevivientes y no sobrevivientes con infarto agudo de miocardio no reperfundido y conocer los predictores de mortalidad intrahospitalaria. MÉTODOS: Estudio de cohorte retrospectiva que incluyó pacientes con infarto agudo de miocardio no reperfundido de octubre de 2005 a agosto de 2020. Se clasificaron los pacientes de acuerdo a su estado de sobrevida y se compararon las características clínicas, tratamientos y desenlaces para poder identificar los predictores de mortalidad intrahospitalaria. RESULTADOS: Se incluyeron 2442 pacientes con infarto agudo de miocardio no reperfundido, en los que se encontró una mortalidad de 12.7% vs 7.2% los que si recibieron tratamiento de reperfusión. La principal razón para no recibir tratamiento de reperfusión fue el retraso en la atención médica (96.1%). Los no sobrevivientes tuvieron mayor edad, fueron mujeres y tuvieron mayor frecuencia de diabetes, hipertensión y fibrilación atrial. El tronco de la coronaria izquierda y la enfermedad trivascular fueron más frecuentes en los que no sobrevivieron. Los pacientes que no sobrevivieron desarrollaron más insuficiencia cardiaca, reinfarto, bloqueo atrioventricular, sangrados, evento vascular cerebral y muerte. Los principales predictores de mortalidad intrahospitalaria fueron: insuficiencia renal (HR 3.41), tensión arterial sistólica al ingreso < 100 mmHg (HR 2.26) y fracción de eyección del ventrículo izquierdo < 40% (HR 1.97). CONCLUSIONES: Los pacientes con infarto de miocardio no reperfundido tienen mayor mortalidad y desenlaces adversos. Los no sobrevivientes fueron mayores, con más comorbilidades y desarrollaron más desenlaces adversos intrahospitalarios.

COMPARISON OF THE PREDICTIVE PERFORMANCE OF CARDIOGENIC SHOCK SCORES IN A REAL-WORLD LATIN AMERICA COUNTRY.

ABSTRACT: Background : Mortality in cardiogenic shock (CS) is up to 40%, and although risk scores have been proposed to stratify and assess mortality in CS, they have been shown to have inconsistent performance. The purpose was to compare CS prognostic scores and describe their performance in a real-world Latin American country. Methods : We included 872 patients with CS. The Society for Cardiovascular Angiography and Interventions (SCAI), CARDSHOCK, IABP-Shock II, Cardiogenic Shock Score, age-lactate-creatinine score, Get-With-The-Guidelines Heart Failure score, and Acute Decompensated Heart Failure National Registry scores were calculated. Decision curve analyses were performed to evaluate the net benefit of the different scoring systems. Logistic and Cox regression analyses were applied to construct area under the curve (AUC) statistics, this last one against time using the Inverse Probability of Censoring Weighting method, for in-hospital mortality prediction. Results: When logistic regression was applied, the scores had a moderate-good performance in the overall cohort that was higher AUC in the CARDSHOCK ( c = 0.666). In acute myocardial infarction-related CS (AMI-CS), CARDSHOCK still is the highest AUC (0.68). In non-AMI-CS only SCAI (0.668), CARDSHOCK (0.533), and IABP-SHOCK II (0.636) had statistically significant values. When analyzed over time, significant differences arose in the AUC, suggesting that a time-sensitive component influenced the prediction of mortality. The highest AUC was for the CARDSHOCK score (0.658), followed by SCAI (0.622). In AMI-CS-related, the highest AUC was for the CARDSHOCK score (0.671). In non-AMI-CS, SCAI was the best (0.642). Conclusions : Clinical scores show a time-sensitive AUC, suggesting that performance could be influenced by time and the type of CS. Understanding the temporal influence on the scores could provide a better prediction and be a valuable tool in CS.

Anxiety, depression, perceived executive function and sugar sweetened beverages: a causal mediation analysis in Mexican young adults.

There is the notion that dysregulation of executive function (EF), which disrupts behavior and cognitive processes, may explain the emotional impairment which leads to increasing sugar sweetened beverages (SSBs) intake. We aimed to test whether anxiety and depression mediate the association between self-reported problems in EF and sugar sweetened beverage intake in Mexican adults between 18-40 years. An open survey advertised as a 'mental health and sugar sweetened beverages study' was conducted, participants were recruited through Facebook ads. Males and females, between 18-40 years, able to read and write, and currently residing in Mexico were included. We analyzed data using causal mediation analysis with latent variables using a structural equation modelling framework. Significant indirect effects were found for somatic symptoms of depression (ß = 6.601, SE = 2.657, p < .05) and anxiety (ß = .679, SE =.334, p < .05). In depression model no significant direct effects of EF were found in the depression model, however they were found in the anxiety model (ß = 1.335 SE =.566, p < .05). Somatic symptoms of depression were a total mediator, and anxiety a partial mediator. The results suggest that EF increased the probability of emotional symptoms, which led to a higher consumption of SBBs.

Dynamic Invasive Hemodynamic Congestion Profile Impacts Acute Myocardial Infarction Complicated by Cardiogenic Shock Outcomes: A Real-World Single-Center Study.

BACKGROUND: Cardiogenic shock (CS) commonly complicates the management of acute myocardial infarction (AMI), and it results in high mortality rates. Pulmonary artery catheter (PAC) monitoring can be valuable for personalizing critical-care interventions. We hypothesized that patients with AMI-CS experiencing persistent congestion measures during the first 24 hours of the PAC installment would exhibit worse in-hospital survival rates. METHODS AND RESULTS: We studied 295 patients with AMI-CS between January 2006 and December 2021. The first 24-hour PAC-derived hemodynamic measures were divided by the congestion profiling and the proposed 2022 Cardiovascular Angiography and Interventions (SCAI) classification. Biventricular congestion was the most common profile and was associated with the highest patient mortality rates at all time points (mean 56.6%). A persistent congestive profile was associated with increased mortality rates (hazard ratio [HR] = 1.85; P = 0.002) compared with patients who achieved decongestive profiles. Patients with SCAI stages D/E had higher levels of right atrial pressure (RAP): 14-15 mmHg) and pulmonary capillary wedge pressure (PCWP): 18-20 mmHg) compared with stage C (RAP, 10-11 mmHg, mean difference 3-5 mmHg; P < 0.001; PCWP 14-17 mmHg; mean difference 1.56-4 mmHg; P = 0.011). In SCAI stages D/E, the pulmonary artery pulsatility index (0.8-1.19) was lower than in those with grade C (1.29-1.63; mean difference 0.21-0.73; P < 0.001). CONCLUSIONS: Continuous congestion profiling using the SCAI classification matched the grade of hemodynamic severity and the increased risk of in-hospital death. Early decongestion appears to be an important prognostic and therapeutic goal in patients with AMI-CS and warrants further study.

Impact of face masks during the treadmill exercise tests. / Impacto del uso de la mascarilla durante la realización de la prueba de esfuerzo en tapiz rodante.

INTRODUCTION AND OBJECTIVE: There is little literature on the use of face masks in a treadmill test (TMT) during the COVID-19 pandemic. The objective of this study is to analyze the impact of face masks during a TMT performed during the prepandemic (without face mask) and postpandemic (with face mask) era. METHODS: Retrospective observational unicentric study of patients undergoing TMT. The inclusion criterion were being over 16years old and having performed at least one TMT in the prepandemic and postpandemic period. RESULTS: One thousand six hundred fifty-five patients were included in the study. Nine hundred thirty-five (56.5%) were men and 720 (43.5%) women. The mean age was 57.3±14.9 and the mean follow-up time was 15.4 months. Fifty-three percent patients had arterial hypertension, 20% dyslipidemia, 12% diabetes mellitus, 8% smoking habit, 19% personal history of ischemic heart disease, 5% COPD, 8% bronchial asthma, and 8% atrial fibrillation. In almost all the variables studied in PE, including the appearance of ventricular arrhythmias, no significant differences were found, neither by age nor sex, except for the existence of a very slight decrease in exercise capacity with mask use in older patients (>65years). CONCLUSIONS: The use of surgical or FFP2 face masks during the TMT did not affect functional capacity, blood pressure, heart rate, or increased ventricular arrhythmias.

GEN: Generative Equivariant Networks for Diverse Image-to-Image Translation.

Image-to-image (I2I) translation has become a key asset for generative adversarial networks. Convolutional neural networks (CNNs), despite having a significant performance, are not able to capture the spatial relationships among different parts of an object and, thus, do not qualify as the ideal representative model for image translation tasks. As a remedy to this problem, capsule networks have been proposed to represent patterns for a visual object in such a way that preserves hierarchical spatial relationships. The training of capsules is constrained by learning all pairwise relationships between capsules of consecutive layers. This design would be prohibitively expensive both in time and memory. In this article, we present a new framework for capsule networks to provide a full description of the input components at various levels of semantics, which can successfully be applied to the generator-discriminator architectures without incurring computational overhead compared to the CNNs. To successfully apply the proposed capsules in the generative adversarial network, we put forth a novel Gromov-Wasserstein (GW) distance as a differentiable loss function that compares the dissimilarity between two distributions and then guides the learned distribution toward target properties, using optimal transport (OT) discrepancy. The proposed method-which is called generative equivariant network (GEN)-is an alternative architecture for GANs with equivariance capsule layers. The proposed model is evaluated through a comprehensive set of experiments on I2I translation and image generation tasks and compared with several state-of-the-art models. Results indicate that there is a principled connection between generative and capsule models that allows extracting discriminant and invariant information from image data.

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.